WO2021135393A1 - 一种图像分析装置及其成像方法 - Google Patents

一种图像分析装置及其成像方法 Download PDF

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Publication number
WO2021135393A1
WO2021135393A1 PCT/CN2020/115420 CN2020115420W WO2021135393A1 WO 2021135393 A1 WO2021135393 A1 WO 2021135393A1 CN 2020115420 W CN2020115420 W CN 2020115420W WO 2021135393 A1 WO2021135393 A1 WO 2021135393A1
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Prior art keywords
image
tested
sample
target
imaging device
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PCT/CN2020/115420
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English (en)
French (fr)
Inventor
叶波
唐玉坤
邢圆
祁欢
周慕昭
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深圳迈瑞生物医疗电子股份有限公司
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Priority to CN202080003734.9A priority Critical patent/CN112469984B/zh
Publication of WO2021135393A1 publication Critical patent/WO2021135393A1/zh

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    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B21/00—Microscopes
    • G02B21/36—Microscopes arranged for photographic purposes or projection purposes or digital imaging or video purposes including associated control and data processing arrangements

Definitions

  • the embodiment of the present invention relates to in vitro diagnostic technology, and relates to but not limited to an image analysis device and an imaging method thereof.
  • the image analysis equipment When the image analysis equipment performs cell image detection on a blood sample, it moves the glass slide from the previous shooting position to the target shooting position. After a certain period of time, the blood cells are photographed at the target shooting position.
  • the mechanical device since it takes a period of time from the end of the movement of the mechanical device to the complete standstill of the mechanical device, during this period of time, the mechanical device is actually continuously shaking, and the amplitude of the shaking may be as much as several micrometers.
  • a high-power lens with a certain magnification such as a 100x high-power lens
  • you start auto-focusing or shoot directly during this shaking process the captured image will appear blurred due to the shaking. Therefore, by waiting for a period of time T, it is possible to avoid blurring as much as possible.
  • the waiting time T after each movement is a fixed value set, so that the following situations exist in the shooting process: the target to be analyzed is started to be captured when the shaking of the mechanical device does not meet the shooting conditions. Image, or the mechanical device has stopped shaking before waiting for the time period T, but the image analysis equipment will still wait for the time period T before starting to capture the target image to be analyzed. Therefore, in the above solution, either the photographed cell image is blurry, or there is a waste of time and resources, resulting in low work efficiency of the image analysis device.
  • the embodiment of the present invention provides an image analysis device and an imaging method thereof, which can dynamically adjust the waiting time before starting to capture a target image to be analyzed, and improve the utilization of time resources while ensuring that the captured image is clear.
  • an embodiment of the present invention provides an imaging method for an image analysis device, the image analysis device includes an imaging device, and the method includes:
  • the imaging device Drive the sample to be tested from the first position to the second position, or move the imaging device from the first position to the second position, where the second position means that the target in the sample to be tested is located in the imaging range of the imaging device Obtain the characterization information of the second position, and the characterization information of the second position determines the first waiting time; after the sample to be tested stays in the second position for the first waiting time, it is obtained by the imaging device The image of the target in the sample to be tested is used as the target image of the target.
  • an embodiment of the present invention provides an imaging method for an image analysis device, the analysis device includes an imaging device, and the method includes:
  • the imaging device takes at least two images of the target in the sample to be tested located at the second position as reference images of the target;
  • the imaging device When there is no image meeting the condition in the image, the imaging device continues to take an image of the target object in the sample to be tested located at the second position as a reference image of the target object;
  • an image of the target object in the sample to be tested at the second position is acquired as the target image of the target object.
  • an embodiment of the present invention provides an image analysis device, and the device includes:
  • Imaging device mobile device and controller
  • the imaging device includes a camera and a lens group, and is configured to take an image of a target in a sample to be tested;
  • the mobile device has a platform on which the sample to be tested is placed and a driving part, the lens group is located between the camera and the platform, and the driving part makes the platform and the imaging device move relative to each other for imaging The device shoots the target image of the specific area of the sample to be tested;
  • the controller is coupled with the imaging device and the mobile device, and is configured to:
  • an embodiment of the present invention provides an image analysis device, and the device includes:
  • Imaging device mobile device and controller
  • the imaging device includes a camera and a lens group, and is configured to take an image of a target in a sample to be tested;
  • the mobile device has a platform on which the sample to be tested is placed and a driving part, the lens group is located between the camera and the platform, and the driving part makes the platform and the imaging device move relative to each other for imaging The device shoots the target image of the specific area of the sample to be tested;
  • the controller is coupled with the imaging device and the mobile device, and is configured to:
  • the embodiment of the present invention provides a storage medium with a computer program stored on the storage medium, and when the computer program is executed by a controller, the steps of the image analysis device imaging method executed by the above-mentioned image analysis device are implemented.
  • the image of the target in the sample to be analyzed at the second position is acquired.
  • the image of the target in the sample to be tested was acquired by the imaging device as the target image of the target, and the first waiting time was determined by the characterization information of the second position , So that the waiting time is adapted to the moving position, while ensuring that the captured image is clear, the utilization of time resources is improved, and the working efficiency of the image analysis equipment is improved.
  • Figure 1 is a schematic diagram of a cell image provided by an embodiment of the present invention.
  • FIG. 2A is a schematic diagram of an optional structure of an image analysis device provided by an embodiment of the present invention.
  • 2B is a schematic diagram of an optional structure of an image analysis device provided by an embodiment of the present invention.
  • FIG. 3 is a schematic diagram of an optional structure of an image analysis device provided by an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of an optional structure of an image analysis device provided by an embodiment of the present invention.
  • FIG. 5 is a schematic diagram of an optional structure of a sample analysis system provided by an embodiment of the present invention.
  • FIG. 6 is a schematic diagram of an optional flow chart of an imaging method of an image analysis device provided by an embodiment of the present invention.
  • FIG. 7 is a schematic diagram of the relative movement of the sample to be tested and the imaging device according to an embodiment of the present invention.
  • FIG. 8A is an optional flowchart of an imaging method of an image analysis device provided by an embodiment of the present invention.
  • FIG. 8B is a schematic diagram of an optional flow chart of an imaging method of an image analysis device provided by an embodiment of the present invention.
  • FIG. 9 is a schematic diagram of a reference image provided by an embodiment of the present invention.
  • FIG. 10 is an optional schematic diagram of determining an image that satisfies a stable condition provided by an embodiment of the present invention.
  • FIG. 11A is an optional schematic diagram of determining an image that satisfies a stable condition according to an embodiment of the present invention.
  • FIG. 11B is an optional schematic diagram of determining an image that satisfies a stable condition provided by an embodiment of the present invention.
  • FIG. 12 is a schematic diagram of registration provided by an embodiment of the present invention.
  • FIG. 13 is an optional schematic diagram of determining an image that satisfies a stable condition provided by an embodiment of the present invention.
  • FIG. 14 is a schematic diagram of an optional curve of a fitting curve provided by an embodiment of the present invention.
  • 15 is a schematic diagram of an optional curve of a fitting curve provided by an embodiment of the present invention.
  • FIG. 16 is a schematic diagram of an optional curve of a fitting curve provided by an embodiment of the present invention.
  • FIG. 17 is a schematic diagram of an optional curve of a fitting curve provided by an embodiment of the present invention.
  • FIG. 18 is a schematic diagram of an optional flow chart of an imaging method of an image analysis device provided by an embodiment of the present invention.
  • 19 is a schematic diagram of an optional flow chart of an imaging method of an image analysis device provided by an embodiment of the present invention.
  • 20 is a schematic diagram of an optional flow chart of an imaging method of an image analysis device provided by an embodiment of the present invention.
  • FIG. 21 is an optional flowchart of an imaging method of an image analysis device provided by an embodiment of the present invention.
  • 22 is a schematic diagram of an optional flow chart of an imaging method of an image analysis device provided by an embodiment of the present invention.
  • FIG. 23 is an optional flowchart diagram of an imaging method of an image analysis device according to an embodiment of the present invention.
  • 24 is a schematic diagram of an optional flow chart of an imaging method of an image analysis device provided by an embodiment of the present invention.
  • FIG. 25 is a schematic diagram of an optional flowchart of an imaging method of an image analysis device according to an embodiment of the present invention.
  • the process of capturing blood cell images through image analysis equipment includes: using a low power lens (for example: 10 times) to locate the white blood cells in the blood smear, and then using a high power lens (for example: 100 times) to locate the low power lens to The white blood cells are photographed one by one.
  • a low power lens for example: 10 times
  • a high power lens for example: 100 times
  • the last shooting position is A (X1, Y1)
  • the current shooting position is B (X2, Y2).
  • the image analysis equipment controls the movement of the imaging device or the slide to change the shooting position from A Move to position B. Due to the mechanical movement of the imaging device or the glass slide of the image analysis equipment, the whole or part of the components in the image analysis equipment is jittered for a period of time, and the amplitude of the jitter can reach several micrometers.
  • the shooting depth of field is small, and the shaking of the image analysis device can cause the captured cell image to appear blurry, as shown in FIG. 1. Therefore, in order to avoid blurring of the captured cell image, when the image analysis device moves to the B position, it needs to wait for a period of time T before starting to shoot.
  • the waiting time T will be the maximum waiting time that can clearly photograph all white blood cells, for example: the time corresponding to the largest interval in the interval between moving and photographing each white blood cell. In other words, regardless of the distance between the A position and the B position, the waiting time T is the same.
  • the image analysis device if the interval between position A and position B is less than the maximum interval, even when the image analysis device has stabilized and is not shaking, the image analysis device is still waiting until the waiting time is T, then it will take the image to be analyzed The target image will cause a waste of time, reduce the working efficiency of the image analysis device, and thus cannot meet the needs of users.
  • an imaging method for an image analysis device includes an imaging device, and the method includes: providing a sample to be tested; driving the sample to be tested to move from a first position to a second position, or the imaging device The first position is moved to the second position, where the second position is the position of the target in the sample to be measured within the shooting range of the imaging device; the characteristic information of the second position is acquired, and the second position is The characterization information determines the first waiting time; after the sample to be tested stays at the second position for the first waiting time, the imaging device acquires an image of the target in the sample to be tested as the target image of the target.
  • the first waiting time is dynamically determined by the characterization information of different second positions, that is, it is determined when the imaging device acquires the target image of the target object.
  • the first waiting time is not a fixed value, but is constantly changing according to the characteristic information of different second positions. The method improves the utilization of time resources while ensuring that the captured image is clear, thereby improving the working efficiency of the image analysis device.
  • the image analysis device is used for image shooting and analysis of the target in the sample to be tested, and the result of the image reading is obtained.
  • the image analysis device may be an automated image reader.
  • the sample to be tested may include: blood smear, bone marrow smear, pathological section, bacterial-containing sample smear, urine sediment sample, etc., and may also be smears of other body fluids.
  • the target can be blood cells, such as white blood cells; when the sample to be tested is a bone marrow smear, the target can be bone marrow cells; when the sample to be tested is a pathological section, the target can be a certain diseased tissue ;
  • the sample to be tested is a sample smear containing bacteria, the target can be bacteria; when the sample to be tested is a urine sediment sample, it may not be made into a smear, such as: urine can be deposited in the container to form urine sediment
  • the target is a certain kind of sediment in the urine.
  • the type of the sample to be tested and the corresponding target are not limited in any way.
  • the image analysis equipment 200 includes an imaging device 201, a mobile device 202, and a controller 203.
  • the imaging device 201 includes a camera 2011 and a lens group 2012
  • the mobile device 202 includes a platform 2021 for placing a sample to be tested and a driver. ⁇ 2022.
  • the imaging device 201 is used to take an image of the target in the sample to be tested;
  • the moving device 202 is used to move the sample to be tested relative to the imaging device 201, so that the imaging device 201 captures an image of a target in a specific area of the sample to be tested;
  • the controller 203 is configured to control the imaging device and the mobile device in the image analysis device 200 and process the data in the image analysis device 200.
  • the image analysis device 200 further includes: a vibration detection sensor 208, which can detect the mechanical movement of the image analysis device 200 or some of its components, and convert the detected mechanical quantity into electricity data.
  • a vibration detection sensor 208 which can detect the mechanical movement of the image analysis device 200 or some of its components, and convert the detected mechanical quantity into electricity data.
  • the image analysis device provided in the embodiment of the present invention is further described by taking the sample to be tested as a blood smear as an example, and the following description is also applicable to other samples to be tested.
  • the imaging device is used to take an image of cells in a specific area of the blood smear.
  • the image analysis device 200 further includes: an identification device 204, a slide clamping device 205, and a slide recovery device 206.
  • the identification device 204 is used to identify the identity information of the smear
  • the slide clamping device 205 is used to clamp the smear from the identification device 204 to the mobile device 202 for testing
  • the slide recovery device 206 is used to place the tested smear .
  • the image analysis equipment 200 also includes a slide basket loading device 207 for loading a slide basket containing the smears to be tested, and the slide gripping device 205 is also used for placing the slide basket loading device 207 in the slide basket loaded on the slide basket loading device 207.
  • the smear to be tested is clipped to the identification device 204 for identity information identification.
  • the lens group may include a first objective lens 401 and a second objective lens 402.
  • the first objective lens 401 may be, for example, a 10 times objective lens
  • the second objective lens 402 may be, for example, a 100 times objective lens.
  • the lens group may further include a third objective lens 403, and the third objective lens 403 may be, for example, a 40x objective lens.
  • the lens group may also include eyepieces.
  • the moving device 202 is used to move the smear 21 relative to the camera 2011 so that the camera 2011 captures a cell image of a specific area of the smear 21. Among them, the prepared smear 21 that has not been photographed is loaded on the slide glass basket 20.
  • the cells in the blood smear may include white blood cells, red blood cells, platelets, etc., which can be obtained by treating whole blood drawn from animals or humans with diluents, hemolytic agents, and the like.
  • the classification of white blood cells can include three classifications, four classifications and five classifications. Taking the three classifications as an example, it means that white blood cells are divided into three major types, which are divided into small cell groups (cell groups composed of lymphocytes (Lymphocytes, Lyn)) and intermediate cell groups (monocytes) through a certain dilution. (Monocyte, Mon) cell group) and large cell group (Granulocyte), and get the number of lymphocytes, monocytes and granulocytes in the blood sample.
  • small cell groups composed of lymphocytes (Lymphocytes, Lyn)
  • monocytes intermediate cell groups
  • Gnulocyte large cell group
  • Leukocytes can be directly classified into neutrophils (Neu), lymphocytes (Lyn), eosinophilia (Eos), and basophils by means of a certain dilution and chemical staining or impedance method.
  • Cells basoophilicgranulocyte, Bas or Baso
  • monocytes Mon.
  • the reading result of the image analysis device 200 includes: analysis information, white blood cells, red blood cells, and platelets.
  • the detection results corresponding to white blood cells include cell images of the following cells: neutrophil granulocytes, neutrophil rod-shaped granulocytes, lymphocytes, monocytes, eosinophils, basophils, and neutral Myeloblasts, neutrophils, promyelocytic cells, primitive cells, heterosexual lymphocytes, plasma cells, etc.
  • the image analysis device 200 provided in the embodiment of the present invention can be applied to the sample analysis system 500 shown in FIG. 5, as shown in FIG. 5, the sample analysis system 500 includes blood An analyzer 501, a smear preparation device 502, an image analysis device 200, and a control device 504.
  • the blood analyzer 501 is used to perform blood routine testing on the blood smear to be tested to obtain blood routine results.
  • the smear preparation device 502 is used to prepare smears of blood smears to be tested.
  • the image analysis device 200 is used for image capture and analysis of the cells in the smear to obtain the reading result.
  • the control device 504 is in communication connection with the blood analyzer 501, the smear preparation device 502, and the image analysis device 200, collects the reading results of the image analysis device 200 and the blood routine results of the blood analyzer 501, and compares the collected reading results and blood Routine results are processed.
  • the sample analysis system 500 also includes a first transfer track 505 and a second transfer track 506.
  • the first transfer track 505 is used to transport a test tube rack 10 that can hold a plurality of test tubes 11 loaded with blood samples to be tested from the blood analyzer 501 to the coating.
  • the slide preparation device 502 and the second transport track 505 are used to transport the slide basket 20 that can load a plurality of prepared smears 21 from the smear preparation device 502 to the image analysis device 200.
  • the control device 504 is electrically connected to the first transmission track 505 and the second transmission track 506 and controls its actions.
  • the sample analysis system 500 also includes feeding mechanisms 507 and 508 respectively corresponding to the blood analyzer 501 and the smear preparation device 502.
  • Each feeding mechanism 507 and 508 includes loading buffer areas 171 and 181, and feeding detection areas 172 and 183. And unload the cache areas 173 and 183.
  • the test tube rack 10 When the blood smear to be tested on the test tube rack 10 needs to be transported to the blood analyzer 501 for testing, the test tube rack 10 is first transported from the first transport track 505 to the loading buffer area 171, and then from the loading buffer area 171 to The feed detection area 172 is detected by the blood analyzer 501. After the detection is completed, it is unloaded from the feed detection area 172 to the unloading buffer area 173, and finally enters the first transmission track 505 from the unloading buffer area 173.
  • the test tube rack 10 needs to be transported to the smear preparation device 502 to prepare the smear.
  • the test tube rack 10 is first transported from the first transfer track 505 to the loading
  • the buffer area 181 is then transported from the loading buffer area 181 to the feed detection area 182 to prepare smears by the smear preparation device 502.
  • the smear preparation is completed, it is unloaded from the feed detection area 182 to the unloading buffer area 183. Finally, it enters the first transmission track 505 from the unloading buffer area 183.
  • the smear preparation device 502 stores the prepared smear 21 in the slide glass basket 20, and transports the slide glass basket 20 containing the smear 21 to be tested to the image analysis device 200 through the second transfer track 506, and the image analysis device 200
  • the cells in the blood smear on the test smear 21 are imaged and analyzed.
  • the smear preparation device 502 can obtain the sample information of the blood smear device in the test tube from the label of the test tube on the test tube rack, and will carry the barcode, two-dimensional code, etc. of the sample information.
  • the information mark is sprayed on the smear.
  • the embodiments of the present invention are not limited to the methods and hardware provided, and there may be multiple implementation manners, such as providing a storage medium (stored with programs or instructions for executing the imaging method provided by the embodiments of the present invention).
  • FIG. 6 provides a schematic flowchart of an imaging method of an image analysis device, including:
  • S601 Provide samples to be tested
  • the sample to be tested may be a blood smear, and the blood smear is prepared from the blood sample to be tested.
  • S602 Drive the sample to be tested to move from the first position to the second position, or the first position of the imaging device to move to the second position, where the second position means that the target in the sample to be tested is located in the imaging device The location within the shooting range;
  • the sample to be tested may be a blood smear
  • the target object may be any one or more of cells in the blood smear, such as white blood cells, red blood cells and/or platelets.
  • the first shooting position aligned by the imaging device is position A
  • the second shooting position aligned by the imaging device is position B by moving the imaging device or the sample to be tested.
  • the position A may be referred to as the first position
  • the position B may be referred to as the second position.
  • the same objective lens can be used.
  • the direction of moving the imaging device or the sample to be measured may include one or a combination of one or more of the X direction, the Y direction, and the Z direction.
  • S603 Acquire characterization information of the second location, where the characterization information of the second location determines the first waiting time;
  • the first waiting time determined correspondingly according to the characteristic information may also be different.
  • the first waiting time corresponding to different second positions is not a fixed value, but dynamically changes with the acquired second position characteristic information, that is, the first waiting time can be dynamically determined according to the actual situation of the moving position.
  • the sample to be tested is a blood smear
  • the first waiting time is ⁇ T1
  • the first waiting time is ⁇ T2
  • the first waiting time is ⁇ T3
  • the first waiting time is ⁇ T3
  • ⁇ T1, ⁇ T2, ⁇ T3 may be the same or different, and it changes dynamically according to the actual movement, not a fixed value .
  • the imaging device After the sample to be tested stays at the second position for the first waiting period, the imaging device acquires an image of the target in the sample to be tested as the target image of the target.
  • the sample to be tested stays at the second position for the first waiting time, so that the image analysis device is gradually stabilized, that is, the image analysis device no longer shakes, or the degree of shake is small, but the target object acquired at this time
  • the target image quality has been able to meet the needs. Therefore, after the first waiting period, a clear target image of the target can be obtained.
  • the jitter of the image analysis equipment may include: the overall jitter of the image analysis equipment generated based on the movement of the sample to be tested or the imaging device, or the jitter of some parts, such as the jitter of a moving part, which may be: the jitter of the sample to be tested, Or the jitter of the imaging device, etc.
  • the above method improves the utilization rate of time resources and improves the working efficiency of the image analysis device while ensuring that the target image of the acquired target is clear.
  • S6031A The sample to be tested or the imaging device moves to the second position, the imaging device takes at least two reference images of the target in the sample to be tested, and the feature information of the reference image is used as the second Characteristic information of the location;
  • the feature information includes: one or more of pixel value, sharpness index, and position information.
  • the imaging device can start to take the reference image immediately when the sample to be tested or the imaging device moves to the second position; it can also be when the sample to be tested or the imaging device moves to the second position and the second waiting period has elapsed. After that, start to take the reference image.
  • the second waiting time period is the time when the sample to be tested moves to the second position or the time when the imaging device moves to the second position to the time when the reference image of the target in the sample to be tested is acquired The interval between.
  • the first waiting time is the time when the sample to be tested moves to the second position or the time when the imaging device moves to the second position to the time when the target image of the target in the sample to be tested is acquired.
  • the first waiting time includes the second waiting time.
  • the image analysis device can periodically shoot the reference image, and can determine the jitter of the image analysis device while shooting the reference image, and determine the first waiting time.
  • S6032A Determine the first waiting time according to the change of the characterization information of the second location.
  • the first waiting time is determined according to the change of the characteristic information of the reference image, that is, the change of the characteristic information of the reference image is used to determine when the image analysis device will be stable and no jitter will occur, so as to obtain the The timing of the target image of the target.
  • the above S6032A, as shown in FIG. 8B, may also include the following steps:
  • S6032A1 Based on the feature information of at least two reference images, determine whether there is an image that meets the stabilization condition among the obtained reference images;
  • the first waiting period is determined.
  • the multiple consecutive images are multiple images obtained by continuous shooting, which may be at least 3, or 4, 5, 6, 8 and so on.
  • the acquisition of reference images includes: image 1, image 2, image 3...image 35.
  • image 35 meets the stabilization condition, it means that the image analysis device is stable and no longer shakes.
  • the image analysis device stops taking the reference image and acquires the target The target image of the object.
  • a new reference image is continuously taken, and the jitter condition of the image analysis device is continuously determined based on the new reference image.
  • Obtaining reference images includes: image 1, image 2, image 3...image 35 obtained by continuous shooting, if the latest reference images obtained by continuous shooting, such as: image 33, image 34, and image 35, all meet the stable conditions .
  • the first waiting time can be determined, and it also indicates that the image analysis device has stabilized and no longer shakes, and the image analysis device stops shooting the reference image, and acquires the target image of the target object.
  • the above-mentioned stabilization condition is not met, then continue to take a new reference image, and determine the jitter condition of the image analysis device based on the new reference image.
  • the judging whether there is an image that meets the stabilization condition in the obtained reference image based on the feature information of at least two reference images includes:
  • the difference of feature information of the adjacent reference images is continuously compared.
  • the difference in feature information corresponding to multiple consecutive reference images all meet the first threshold range, it means that multiple consecutive reference images meet the stabilization condition, which can further indicate that the device is currently stable and can clearly obtain the target of the target. image.
  • the feature information of two adjacent reference images is compared to obtain the feature information difference corresponding to the reference image, such as pixel difference, position information difference, etc.; and the feature information difference corresponding to the reference image is compared with the first A threshold value is used for comparison; if there is a case where the feature information difference is less than the first threshold value, it indicates that there is an image that satisfies the stabilization condition in the reference image.
  • the characteristic information difference may take an absolute value.
  • the characteristic information difference may take an absolute value.
  • the acquired reference images include: image 1, image 2, image 3, image 4, image 5..., the difference between the feature information of image 1 and image 2 (wherein, the feature information difference may take an absolute value), Obtain the feature information difference corresponding to image 2; calculate the difference between the feature information of image 2 and image 3 to obtain the feature information difference corresponding to image 3...
  • the difference of images When the feature information difference corresponding to image 10 is less than the first threshold, or the feature information difference corresponding to image 8, image 9 and image 10 are all less than the first threshold, it is considered that the device is no longer shaking and has stabilized, so the acquisition of reference images is stopped , And stop the calculation of the feature information difference, and obtain the target image of the target object.
  • an image in the reference image is used as a comparison image, and the reference image after the comparison image is compared with the feature information of the comparison image to obtain the feature information difference corresponding to each reference image (wherein, the feature information difference is Can take the absolute value).
  • the contrast image can be any image in the reference image.
  • the reference images in the reference image set include: image 1, image 2, image 3, image 4, image 5..., the contrast image is image 1, and the difference between the feature information of image 1 and image 2 is calculated, that is, the difference 1; Calculate the difference between the feature information of image 1 and image 3, that is, difference 2, compare difference 1 and difference 2, and get the feature information difference corresponding to image 3; calculate the difference between the feature information of image 1 and image 4 , That is, difference 3, compare difference 2 and difference 3 to get the feature information difference corresponding to image 3..., and so on.
  • the shooting of the reference image is stopped, and the calculation of the feature information difference is stopped to obtain The target image of the target.
  • the feature information of the reference image may be one or more of pixel value, sharpness index, and position information.
  • the feature information of the reference image is the pixel value; the pixel difference between two reference images can be calculated.
  • the reference image includes image 901 and image 902, based on each pixel in area Q1 of image 901
  • the value of obtains the pixel value of the image 901, that is, the pixel matrix 1 corresponding to the area Q1.
  • the pixel value of the image 902 is obtained based on each pixel value in the area Q2 in the image 902, that is, the pixel matrix 2 corresponding to the area Q2.
  • the pixel matrix 1 is Pixel matrix 2 is Make difference between pixel matrix 1 and pixel matrix 2, and get the difference matrix:
  • the pixel difference between the two is obtained based on the difference matrix: 0.005.
  • the calculation of the pixel difference of the two images can be calculated based on the comparison of some or all areas in the image.
  • the reference image includes: image 1001, image 1002, image 1003, image 1004..., among which, calculate the difference between two adjacent images 1001 and 1002 Calculate the pixel difference between the two adjacent images 1002 and 1003 as the pixel difference between the pixel difference 1, as the pixel difference corresponding to the image 1002; calculate the pixel difference between the two adjacent images 1002 and 1003, as the pixel difference corresponding to the image 1003; calculate the adjacent two images 1003 and the image
  • the pixel difference 3 between 1004 is taken as the pixel difference corresponding to the image 1004, and so on, the pixel difference corresponding to each reference image currently shot can be obtained.
  • the time window W1 (you can select a period of time forward from the current time as the starting point), if the pixel difference corresponding to all the images in the time window W1 is less than the threshold, it is determined that the corresponding reference images in the time window W1 satisfy Images in stable conditions.
  • the time window can be set to a fixed value as required.
  • the feature information difference is the position difference, such as the amount of translation.
  • the translation amount may be one or a combination of the X-axis translation amount and the Y-axis translation amount.
  • extracting features that remain unchanged from the image is called target features.
  • Determine the position information of the shared target feature in the two images compare the two position information to obtain the translation amount between the two reference images, if the translation amount meets the threshold range of the translation amount, the reference image is characterized There are images satisfying the stabilization condition; wherein, the two reference images may be two adjacent reference images.
  • the extracted target features are the features that appear in the two images that are consistent with the transformations such as scale, rotation, translation, etc., such as line intersections, object edge corners, center of imaginary circle closed area and other extractable features.
  • Features include: point, line and surface, such as the edge of white blood cells.
  • Feature extraction methods can include: Harris (Harris Corner Detector) algorithm, Susan (Susan Corner Detector) algorithm, SIFT feature point extraction, SURF feature point extraction, FAST (Features from Accelerated Segment Test) point feature extraction, Robert line feature extraction, Mser Surface feature extraction and other methods. This embodiment does not impose any limitation on the feature extraction method.
  • the obtained reference images include: image 1101, image 1102, image 1103, image 1104, etc., wherein the feature of cell C1 shared in the image is extracted, and it is determined that cell C1 is in two adjacent ones.
  • the position difference between the position information in the image 1101 and the position information in the image 1102 is also the translation amount 1 of the X axis, which is used as the translation amount corresponding to the image 1102.
  • the position difference between the position information of the cell C1 in the two adjacent images 1102 and the position information in the image 1103 is also the translation amount 2 of the X axis, which is used as the translation amount corresponding to the image 1103.
  • the position difference between the position information of the cell C1 in the two adjacent images 1103 and the position information in the image 1104 is also the translation amount 3 of the X axis, as the translation amount corresponding to the image 1104, and so on to obtain each The amount of translation corresponding to the reference image.
  • the device can be considered stable and jittery Has stopped.
  • the time window W2 select a period of time forward with the current moment as the starting point
  • the X-axis translation amount corresponding to all images in the time window W2 is less than the X-axis translation threshold value
  • the corresponding one in the time window W2 is determined
  • Each reference image is an image that satisfies the stability condition. If the X-axis translation amount corresponding to an image in the time window is greater than the X-axis translation amount threshold, continue shooting the reference image to calculate the corresponding X-axis translation amount, correspondingly slide the time window along the time axis and re-make the above judgment.
  • the time window can be set to a fixed value as required.
  • the reference image includes: image 1101, image 1102, image 1103, image 1104..., wherein the common C1 feature in the image is extracted, and it is determined that cell C1 is in two adjacent images 1101
  • the Y-axis translation amount 1 between the position information of and the position information in the image 1102 is taken as the translation amount corresponding to the image 1102.
  • the Y-axis translation amount 2 between the position information of the cell C1 in two adjacent images 1102 and the position information in the image 1103 is determined as the translation amount corresponding to the image 1102.
  • the Y-axis translation amount 3 between the position information of the cell C1 in two adjacent images 1103 and the position information in the image 1104 is determined, and so on, to obtain the translation amounts corresponding to all the reference images currently shot.
  • the Y-axis translation (absolute value) corresponding to the latest reference image currently obtained is less than the threshold, or the Y-axis translation corresponding to the latest consecutive reference images are all less than the Y-axis translation threshold, it can be considered as the device It has stabilized and the jitter has stopped.
  • the time window W3 select a period of time forward with the current moment as the starting point
  • the Y-axis translation amount corresponding to all the images in the time window W3 is less than the Y-axis translation threshold value
  • the corresponding one in the time window W3 is determined
  • Each reference image is an image that satisfies the stability condition. If the Y-axis translation amount corresponding to an image in the time window is greater than the Y-axis translation amount threshold, continue shooting the reference image to calculate the corresponding Y-axis translation amount, correspondingly slide the time window along the time axis and re-make the above judgment.
  • the time window W2 can be set to a fixed value as required.
  • the X-axis translation amount and the Y-axis translation amount (absolute value) corresponding to the latest reference image currently obtained both meet the corresponding translation threshold range, or the X-axis corresponding to the latest consecutive reference images obtained Both the translation amount of the axis and the Y axis meet the corresponding threshold range of the translation amount, it can be considered that the device has stabilized and the jitter has stopped.
  • the translation amount of the X axis and the Y axis corresponding to the image both meet the threshold requirements, which can better ensure that the analysis device has been stabilized, and the target image can be acquired at this time.
  • the two reference images are registered, and the difference value of the position information between the reference images is calculated. If the difference value meets the threshold range, it means that the reference image has the stability that satisfies the stability.
  • Conditional image the two images may be two adjacent images.
  • Gray-level-based registration that is, directly use the gray information of at least partial images to establish a similarity measure between two images, and then use a search method to find the transformation model that maximizes or minimizes the similarity measure. The parameter value.
  • Registration method two feature-based registration, that is, extracting unchanged features in the image, such as edge points, the center of a closed area, etc., as reference information for the registration of two images, you can refer to the method of extracting the target feature in the previous section. I won’t repeat it here.
  • the adjacent reference images Based on the first registration method, it is possible to search for the relevant areas between the adjacent reference images; in the case that the adjacent reference images overlap based on the relevant areas, it is determined that the adjacent reference images specify The position difference between the positions.
  • the position information is compared to obtain the translation amount.
  • the correlation ⁇ of the overlapping area of two images can be calculated by formula (2):
  • f(x, y) and g(x, y) are the pixel values corresponding to the points (x, y) in the two overlapping regions respectively, versus Respectively, it is the mean value of the pixel values of all the pixels in the two overlapping areas. But it is not limited to the above formula.
  • adjacent reference images include image 1201 and image 1202, fixed image 1201, slide image 1202 on image 1201, and calculate the correlation of the overlapping area for each position sliding, when on image 1201
  • the position obtained by sliding the image 1202 is shown in (1) in FIG. 12, the area A1 in the image 1201 overlaps the area A2 in the image 1202, and the correlation between the area A1 and the area A2 is calculated to obtain the correlation r1.
  • the correlation of the overlapping area is obtained, and the correlation r2 is obtained.
  • the correlation of the overlapping area is obtained, and the correlation r3 is obtained, and so on, to determine the position of the image 1201 and the image 1202 at each sliding position The relevance of overlapping areas. Finally find the most relevant position. If the position shown in (3) in Figure 12 has the largest correlation r3, take the designated point as the upper left vertex of the image as an example, calculate the position information of the upper left vertex of the image 1201 and the position information of the upper left vertex of the image 1201 respectively, and Compare the two position information to get the amount of translation, which can include the amount of translation of the X and Y axes. Based on this, it is determined whether the device has been stabilized.
  • the judging whether there is an image that meets the stabilization condition in the obtained reference image based on the feature information of at least two reference images includes:
  • the degree of dispersion refers to the degree of difference between each feature information or feature information difference.
  • the degree of dispersion can include range, average, and standard deviation.
  • the feature information may be one or more of pixel value, sharpness index, and position information.
  • the characteristic information is used as the sharpness index, such as the focus degree, and the dispersion degree of the focus degree is calculated.
  • 1301, 1302, and 1303 are the focus degrees of the first image, the second image, and the third image in the reference image, respectively, and so on, the curve is a graph of the acquired reference image focus degrees over time.
  • time window W4 select a period of time forward with the current moment as the starting point
  • calculate the dispersion degree of the corresponding reference image focus in the time window W4 calculate the dispersion degree of the corresponding reference image focus in the time window W4, and judge whether the dispersion degree is less than the dispersion degree threshold, if less than the time window
  • the corresponding reference images in W4 meet the stability conditions, and the device can be considered stable.
  • the reference image needs to be retaken to obtain its focus, which is reflected in the need to slide the time window W4 along the time axis in FIG. 13 to recalculate the degree of dispersion for judgment.
  • the time window W4 can be set to a fixed value as required.
  • the degree of dispersion ⁇ can be characterized by formula (3):
  • Imax is the maximum value of the feature information of each reference image or the corresponding feature information difference in the time window W4
  • Imin the minimum value of the feature information of each reference image or the corresponding feature information difference in the time window W4
  • I is from 0 to the current window The average value of the feature information of all reference images or the difference of corresponding feature information.
  • image 10, image 11, and image 12 are images that meet the stabilization conditions, and the device is considered stable and no longer shakes, and the reference image is stopped. Obtain.
  • the dispersion degree of the position information and its difference, the difference of the definition index, the pixel value, etc. can also be calculated.
  • the method is similar to the above embodiment, and no examples are given here.
  • the judging whether there is an image that meets the stabilization condition in the obtained reference image based on the feature information of at least two reference images includes:
  • a curve is obtained based on the characteristic information of the reference image, and it is judged whether the change trend of the curve is flat.
  • obtaining a curve based on the characteristic information of the reference image and judging whether the changing trend of the curve is flat includes the following steps:
  • a fitting curve is obtained based on the characteristic information of the reference image, and the absolute value of the slope of the fitting curve is calculated; the absolute value of the slope of the fitting curve is compared with a third threshold range; if the slope of the fitting curve is If the absolute value meets the third threshold value range, it indicates that the change trend of the curve is flat, that is, there is an image that satisfies the stabilization condition in the reference image, and it can be considered that the analysis device has been stabilized.
  • the absolute value of the slope change of the fitted curve is also calculated, and if the absolute value of the slope of the fitted curve and the absolute value of the slope change of the fitted curve both meet the threshold range, the change trend of the curve is characterized Flat, that is, there is an image that satisfies the stabilization condition in the reference image. It can more accurately determine whether the image analysis equipment is stable.
  • the slope of the fitted curve may be the first derivative of the fitted curve
  • the change in the slope of the fitted curve may be the second derivative of the fitted curve
  • the obtained characteristic information of each reference image is plotted over time, and the point above the curve is fitted to the envelope L1.
  • the current time can also be used as the starting point to select the characteristic information over time in a period of time.
  • the changing curve fits the envelope.
  • the envelope equation m s(n), n is time, m is the value of the curve, calculate the first-order derivative s′ and the second-order derivative s′′ of s(n), where, when the first-order derivative is larger, it means The greater the descending slope of the curve; the greater the second-order derivative, the greater the change in the slope of the curve.
  • S1 and S2 can be set empirical values.
  • the fitting curve may be based on the envelope of all feature information of the currently acquired reference image, or may be based on the envelope of part of the feature information.
  • the feature information of a plurality of consecutive reference images is selected for fitting to obtain a fitting curve. For example, if the number of selection is 3, when the newly acquired image is image 3, then the characteristic information of image 1, image 2 and image 3 will be fitted to obtain the fitting curve 1, and the last point or continuous number on the fitting curve will be calculated.
  • the slope of each point is used to determine whether the newly acquired image satisfies the stability condition. If it is not satisfied, continue to obtain a new reference image 4, and then fit the characteristic information of image 2, image 3 and image 4 to obtain the fitting curve 2, and then calculate the last point or multiple consecutive points on the fitting curve
  • the slope is used to determine whether the newly acquired image meets the stability condition. If the slope is less than the corresponding threshold, image 2, image 3, and image 4 are considered to meet the stability condition, indicating that the analysis device has stabilized and no new reference images are acquired.
  • the fitting curve is a connection line between part of the feature information of a plurality of consecutive images.
  • time window W5 select a period of time forward with the current moment as the starting point
  • select the corresponding point 1502 (current point) on the curve at the current moment and select a point on the curve in the time window 1501 (may also be multiple points), based on these points to fit the curve
  • calculate the slope of the curve and determine whether the reference image in the time window W5 satisfies the stable condition based on the slope. If the stabilization condition is met, stop taking the reference image, consider that the device is stable, and obtain the target image of the target. If it is not satisfied to continue shooting the reference image, the time window continues to slide to the right along the time axis to continue the judgment.
  • the smaller the slope the more stable the characteristic fitting curve, and the smaller the change in image feature information.
  • the range of feature information of consecutive multiple images is calculated, new range can be continuously obtained according to the obtained new reference image, and each range is fitted to obtain a fitting curve.
  • the first range is obtained based on the feature information in the time window W6, and new reference images are continuously shot. Therefore, the time window W6 is moved to the right along the time axis to obtain the second range, The third extreme..., where the last feature information in the time window W6 is the feature information of the currently acquired reference image, and the curve L3 is obtained by fitting the extreme points in the dashed box shown in Figure 16, and the fitting is calculated The absolute value of the slope of the last point on the curve or the last consecutive points. If the absolute value of the slope is less than the corresponding threshold, there is an image that satisfies the stability condition in the reference image, and the device has stabilized. If not, continue to take the reference image, calculate the new range, and fit the curve for judgment.
  • the absolute value of the difference between the maximum value of the feature information and the mean value of the feature information in the consecutive images is taken, and the absolute value of each difference is fitted to obtain a fitting curve.
  • the mean value is the mean value of the characteristic information of multiple consecutive images or the mean value of the characteristic information of all reference images currently obtained.
  • the absolute value of the difference between the maximum value and the mean value of the feature information in the time window W7 is calculated, the first difference is obtained, and new reference images are continuously obtained, so the time window W7 is continued to move along the time axis to the right .
  • the third difference Using the same calculation method to obtain the second difference, the third difference..., here, the last feature information in the time window W7 is the feature information of the latest reference image currently acquired, based on the points of each difference in the dashed frame Obtain the fitting curve L4, and calculate the absolute value of the slope of the last point or the last consecutive points on the fitting curve. If the absolute value of the slope is less than the corresponding threshold, there is an image that meets the stability condition in the reference image, and the device has stabilized. If it is not satisfied, continue to take the reference image, calculate the new difference, and fit the curve for judgment.
  • the corresponding relationship between the moving distance and/or moving speed and the first waiting period may be set in the image analysis device, and the image analysis device determines the current moving distance and/or the second corresponding to the moving speed according to the set association relationship. One waits for a long time.
  • the moving distance is the length of the moving track. If moving in a straight line, it is the straight line distance between two positions.
  • the size of the first waiting time is directly proportional to the moving speed, that is, the greater the moving speed, the larger the first waiting time, the smaller the moving speed, and the smaller the first waiting time.
  • the size of the first waiting time is directly proportional to the moving distance, that is, the larger the moving distance, the larger the first waiting time, the smaller the moving distance, and the smaller the first waiting time.
  • the moving speed will also be greater, so it will be brought after stopping the movement. The jitter will be more severe, and the first waiting time required will be greater.
  • the image analysis device may further include: a vibration detection sensor; the above S603: acquiring characteristic information of a second position, where the characteristic information of the second position determines the first waiting time;
  • the vibration sensor can receive the mechanical quantity and convert the received mechanical quantity into an electric quantity proportional to it, which is an electromechanical conversion device.
  • the electromechanical conversion types of the vibration sensor may include: electric, piezoelectric, eddy current, inductive, capacitive, resistive, photoelectric, and so on.
  • the embodiment of the present invention does not impose any restriction on the electromechanical conversion type of the vibration sensor.
  • the vibration sensor may include one or a combination of a displacement sensor, a speed sensor, an acceleration sensor, a force sensor, a strain sensor, a torsional vibration sensor, a torque sensor, and the like.
  • the type of the vibration sensor is not limited in any way.
  • the electrical energy data obtained by the vibration sensor electromechanical conversion of the mechanical quantity is vibration data.
  • the vibration data meets the stability condition, it means that the image analysis equipment has been stabilized.
  • the target image can be acquired and the first waiting time can be determined.
  • the first waiting time is the interval between the time when the sample to be tested moves to the second position or the imaging device moves to the second position to the time when the target image of the target object is acquired.
  • the vibration sensor is a displacement sensor
  • the vibration data detected by the vibration sensor is the displacement of the image analysis device.
  • the stability condition is: less than the displacement threshold. When the displacement detected by the vibration sensor is less than the displacement threshold, it is determined that the vibration data meets the stability condition. .
  • the vibration sensor is a speed sensor
  • the vibration data detected by the speed sensor is the speed of the image analysis device.
  • the stability condition is: less than the speed threshold. When the speed detected by the vibration sensor is less than the speed threshold, it is determined that the vibration data meets the stability condition. .
  • stabilizing conditions can be set according to actual requirements to determine whether the image analysis device is stable.
  • the imaging method of the image analysis device further includes:
  • S605 Calculate the working time required to determine the first waiting time, and compare the working time with a preset time threshold;
  • a prompt message can be output to give an alarm to remind the user that the current image analysis device may be abnormal.
  • S604 is executed: After the sample to be tested stays in the second position for the first waiting duration, the imaging device acquires the image of the target in the sample to be tested as the The target image of the target object.
  • the imaging device acquires an image of the target in the sample to be tested as the target image of the target, including:
  • An image that meets the stabilization condition in the reference image is selected as the target image of the target object.
  • the image that meets the stabilization condition in the reference image can be directly used as the target image, or an image with better image quality can be selected as the target image.
  • there is no need to take the image again after the first waiting period thereby saving time, reducing the number of times of taking the image analysis device, and improving the efficiency of the device.
  • the imaging device acquires an image of the target in the sample to be tested as the target image of the target, including:
  • the sample to be tested stays at the second position for the first waiting time
  • the imaging device is controlled to take an image of the target in the sample to be tested as the target image of the target.
  • the image analysis device determines that the image analysis device is stable, and then performs shooting again, and shoots the image of the target object in the sample to be tested at the second position as the target image. This can effectively guarantee the quality of the target image obtained.
  • an embodiment of the present invention also provides an imaging method for an image analysis device, as shown in FIG. 21, including:
  • S2101 Provide samples to be tested.
  • the sample to be tested may be a blood smear, and the blood smear is prepared from the blood sample to be tested.
  • S2102 Drive the sample to be tested to move from the first position to the second position or the imaging device to move from the first position to the second position.
  • the second position is a position in the sample to be tested where the target is located within the shooting range of the imaging device.
  • the sample to be tested may be a blood smear
  • the target object may be any one or more of cells in the blood smear, such as white blood cells, red blood cells and/or platelets.
  • the first shooting position aligned by the imaging device is position A
  • the second shooting position aligned by the imaging device is position B by moving the imaging device or the sample smear to be tested.
  • the position A may be referred to as the first position
  • the position B may be referred to as the second position.
  • the same objective lens can be used. For example, in the process of taking pictures of white blood cells in different positions in a blood smear under a high power lens, the high power lens is not replaced, and the same high power lens is used to complete the shooting process.
  • the imaging device takes at least two images of the target in the sample to be tested located at the second position as reference images of the target;
  • the imaging device can start to take the reference image immediately when the sample to be tested or the imaging device moves to the second position; it can also be when the sample to be tested or the imaging device moves to the second position and the second waiting period has elapsed. After that, start to take the reference image.
  • the second waiting time period is the time when the sample to be tested moves to the second position or the time when the imaging device moves to the second position to the time when the reference image of the target in the sample to be tested is acquired The interval between.
  • the image analysis device can periodically shoot the reference image, and can determine the jitter of the image analysis device while shooting the reference image, and determine whether to obtain the target image.
  • S2104 Based on the feature information of the reference image, determine whether there is an image that meets the stability condition in the reference image;
  • the feature information includes: one or more of pixel value, sharpness index, and position information.
  • the image analysis device judges when the image analysis device is stable and no longer shakes according to the change of the characteristic information of the reference image, and then obtains the opportunity to obtain the target image of the target object.
  • execute S2103 the imaging device continues to take the image of the target object in the sample to be tested located at the second position as the reference image of the target object;
  • execute S2105 acquire an image of the target object in the sample to be tested at the second position as the target image of the target object.
  • the multiple consecutive images are multiple images obtained by continuous shooting, which may be at least 3, or 4, 5, 6, 8 and so on.
  • the acquisition of reference images includes: image 1, image 2, image 3...image 35.
  • image 35 meets the stabilization condition, it means that the image analysis device is stable and no longer shakes.
  • the image analysis device stops taking the reference image and acquires the target The target image of the object.
  • a new reference image is continuously taken, and the jitter condition of the image analysis device is continuously determined based on the new reference image.
  • the above S2104 based on the feature information of the reference image, determining whether there is an image that satisfies the stabilization condition in the reference image, as shown in FIG. 22, includes:
  • S2104A Based on the feature information of the at least two reference images, determine whether there is an image that meets the stabilization condition in the obtained reference images.
  • Obtaining reference images includes: image 1, image 2, image 3 ... image 35 obtained by continuous shooting, if the latest reference images obtained by continuous shooting, such as: image 33, image 34, and image 35, all meet the stable conditions , Characterizing that the image analysis device has stabilized and no longer shakes, the image analysis device stops taking the reference image, and acquires the target image of the target object. When the above-mentioned stabilization condition is not met, then continue to take a new reference image, and determine the jitter condition of the image analysis device based on the new reference image.
  • the above S2104A the judging whether there is an image that satisfies the stability condition in the obtained reference image based on the feature information of the at least two reference images, as shown in FIG. 23, includes:
  • SA11 based on the difference of feature information of at least two reference images
  • SA12 If the difference meets the first threshold range, it indicates that there is an image that meets the stabilization condition in the reference image.
  • the difference of feature information of the adjacent reference images is continuously compared.
  • the difference in feature information corresponding to multiple consecutive reference images all meet the first threshold range, it means that multiple consecutive reference images meet the stabilization condition, which can further indicate that the device is currently stable and can clearly obtain the target of the target. image.
  • the feature information of two adjacent reference images is compared to obtain the feature information difference corresponding to the reference image, such as pixel difference, position information difference, etc.; and the feature information difference corresponding to the reference image is compared with the first A threshold value is used for comparison; if there is a case where the feature information difference is less than the first threshold value, it indicates that there is an image that satisfies the stabilization condition in the reference image.
  • the characteristic information difference may take an absolute value.
  • the characteristic information difference may take an absolute value.
  • the acquired reference images include: image 1, image 2, image 3, image 4, image 5..., the difference between the feature information of image 1 and image 2 (wherein, the feature information difference may take an absolute value), Obtain the feature information difference corresponding to image 2; calculate the difference between the feature information of image 2 and image 3 to obtain the feature information difference corresponding to image 3...
  • the difference of images When the feature information difference corresponding to image 10 is less than the first threshold, or the feature information difference corresponding to image 8, image 9 and image 10 are all less than the first threshold, it is considered that the device is no longer shaking and has stabilized, so the acquisition of reference images is stopped , And stop the calculation of the feature information difference, and obtain the target image of the target object.
  • an image in the reference image is used as a comparison image, and the reference image after the comparison image is compared with the feature information of the comparison image to obtain the feature information difference corresponding to each reference image (wherein, the feature information difference is Can take the absolute value).
  • the contrast image can be any image in the reference image.
  • the reference images in the reference image set include: image 1, image 2, image 3, image 4, image 5..., the contrast image is image 1, and the difference between the feature information of image 1 and image 2 is calculated, that is, the difference 1; Calculate the difference between the feature information of image 1 and image 3, that is, difference 2, compare difference 1 and difference 2, and get the feature information difference corresponding to image 3; calculate the difference between the feature information of image 1 and image 4 , That is, difference 3, compare difference 2 and difference 3 to get the feature information difference corresponding to image 3..., and so on.
  • the shooting of the reference image is stopped, and the calculation of the feature information difference is stopped to obtain The target image of the target.
  • the above S2104A said determining whether there is an image satisfying the stabilization condition in the obtained reference image based on the feature information of at least two reference images, as shown in FIG. 24, includes:
  • SA21 Calculate the discrete degree of feature information and/or feature information difference of multiple consecutive reference images
  • the degree of dispersion refers to the degree of difference between each feature information or feature information difference.
  • the degree of dispersion can include range, average, and standard deviation.
  • the feature information may be one or more of pixel value, sharpness index, and position information.
  • image 10, image 11, and image 12 are images that meet the stabilization conditions, and the device is considered stable and no longer shakes, and the reference image is stopped. Obtain.
  • the dispersion degree of the position information and its difference, the difference of the definition index, the pixel value, etc. can also be calculated.
  • the method is similar to the above embodiment, and no examples are given here.
  • the above S2104A said determining whether there is an image satisfying the stabilization condition in the obtained reference image based on the feature information of at least two reference images, as shown in FIG. 25, includes:
  • SA31 Obtain a fitting curve based on the feature information of the reference image, and calculate the absolute value of the slope of the fitting curve;
  • SA32 compare the absolute value of the slope of the fitted curve with the third threshold range
  • the absolute value of the slope change of the fitting curve is also calculated, and if the absolute value of the slope of the fitting curve and the absolute value of the slope change of the fitting curve both meet the threshold range, it indicates that there is An image that satisfies the stabilization condition. It can more accurately determine whether the image analysis equipment is stable.
  • the slope of the fitted curve may be the first derivative of the fitted curve
  • the change in the slope of the fitted curve may be the second derivative of the fitted curve
  • the fitting curve may be based on the envelope of all feature information of the currently acquired reference image, or may be based on the envelope of part of the feature information.
  • the feature information of a plurality of consecutive reference images is selected for fitting to obtain a fitting curve. For example, if the number of selection is 3, when the newly acquired image is image 3, then the characteristic information of image 1, image 2 and image 3 will be fitted to obtain the fitting curve 1, and the last point or continuous number on the fitting curve will be calculated. The slope of each point is used to determine whether the newly acquired image satisfies the stability condition.
  • the fitting curve is a connection line between part of the feature information of a plurality of consecutive images.
  • the range of feature information of consecutive multiple images is calculated, new range can be continuously obtained according to the obtained new reference image, and each range is fitted to obtain a fitting curve.
  • the absolute value of the difference between the maximum value of the feature information and the mean value of the feature information in the consecutive images is taken, and the absolute value of each difference is fitted to obtain a fitting curve.
  • the mean value is the mean value of the characteristic information of multiple consecutive images or the mean value of the characteristic information of all reference images currently obtained.
  • the imaging method of the image analysis equipment provided by the embodiment of the present invention, after the sample to be tested is moved to the second position or the imaging device is moved to the second position, the shooting is performed, and the image of the target object in the sample to be tested located at the second position is captured
  • the image is used as a reference image.
  • the reference image includes an image that meets the stabilization condition, the image analysis device is determined to be stable.
  • the reference image includes an image that does not meet the stabilization condition
  • the reference image taken at the second position can be used to accurately determine whether the image analysis equipment is stable, so that the sample to be tested moves to the second position or the imaging device moves to the second position until the time when the target image to be analyzed is obtained
  • the time interval between times changes dynamically according to the second position and is adapted to the moving position. Under the condition that the captured cell image is clear, the utilization rate of time resources is improved, and the working efficiency of the image analysis equipment is improved.
  • the imaging method of the image analysis device provided in the embodiment of the present invention will be illustrated through specific application scenarios.
  • the image analysis equipment moves the position of the blood smear relative to the imaging device from position A (X1, Y1) to position B (X2, Y2) through the moving device or blood smear, and moves the position of the blood smear relative to the imaging device After arriving at position B, a cell image is taken at intervals of a preset time as a reference image.
  • the image analysis device analyzes the captured reference image. If the image analysis device is judged to be stable based on the reference image, it will start autofocus and perform the shooting work, take a picture of the cells located in the shooting area of the blood smear, and obtain the cell image, and Recording the time spent waiting for the image analysis device to stabilize is the first waiting time ⁇ T; otherwise, continue to take the reference image, and determine whether the image analysis device is stable based on the newly taken reference image.
  • the image analysis device may determine whether the image analysis device is stable based on consecutive multiple reference images.
  • the reference images captured by the image analysis device include: image 1, image 2, and image 3. Based on image 1, image 2, and image 3, it is determined whether the image analysis device is stable. When it is determined that the image analysis device is not stable, Then continue to shoot a new reference image: image 4, and determine whether the image analysis device is stable based on image 2, image 3, and image 4, and so on. When it is determined that the image analysis device is stable, no new reference image is taken Image, otherwise continue to shoot a new reference image, and continue to use the new reference image to determine whether the image analysis device is stable.
  • the corresponding reference image may be referred to as an image that satisfies the stability condition.
  • the method for the image analysis device to analyze the reference image includes:
  • the pixel values of the two images are difference, and the X/Y translation amount of the two images is judged after the two images are registered, or the change amount of the focus of the two images is calculated.
  • the image analysis device can be considered stable.
  • ⁇ T exceeds the preset upper limit ⁇ T_max, an alarm will be notified, or no longer waiting, directly start shooting the target image to be analyzed.
  • the interval time for the image analysis device to take the reference image may be the time required for the minimum frame of the camera.
  • the image analysis device determines that the image analysis device is stable when the difference between consecutive N reference images is less than a preset value. Among them, N is greater than or equal to 3.
  • the embodiment of the present invention also provides an image analysis device, which is implemented in the image processing equipment shown in FIGS. 2A, 2B, 3 and 4, as shown in FIG. 2A, including: an imaging device 201, a mobile device 202, and a controller 203;
  • the imaging device 201 includes a camera 2011 and a lens group 2012, and is configured to take an image of a target in the sample to be tested;
  • the moving device 202 has a platform 2021 on which the sample to be tested is placed and a drive unit 2022.
  • the lens group 2022 is located between the camera 2011 and the platform 2021.
  • the drive unit 2022 makes the platform 2021 and the imaging device 201 move relative to each other so that the imaging device 201 can take pictures The target image of the specific area of the sample to be tested;
  • the controller 203 is coupled to the imaging device 201 and the mobile device 202, and is configured to:
  • the acquiring the characterizing information of the second location, and the characterizing information of the second location determining the first waiting time includes:
  • the imaging device takes at least two reference images of the target in the sample to be tested at the second position, and feature information of the reference image is used as the characterization information of the second position;
  • the first waiting time is determined according to the change of the characterization information of the second position.
  • the determining the first waiting period according to the change of the characteristic information of the reference image includes:
  • the first waiting period is determined.
  • the judging whether there is an image that satisfies a stable condition in the obtained reference image based on the feature information of at least two reference images includes:
  • the difference of feature information of the adjacent reference images is continuously compared.
  • the judging whether there is an image that satisfies a stable condition in the obtained reference image based on the feature information of at least two reference images includes:
  • the degree of dispersion meets the second threshold range, it indicates that there is an image that satisfies the stabilization condition in the reference image.
  • the judging whether there is an image that satisfies a stable condition in the obtained reference image based on the feature information of at least two reference images includes:
  • obtaining a curve based on the characteristic information of the reference image, and determining whether the change trend of the curve is flat includes the following steps:
  • a fitting curve is obtained based on the characteristic information of the reference image, and the absolute value of the slope of the fitting curve is calculated; the absolute value of the slope of the fitting curve is compared with a third threshold range; if the slope of the fitting curve is If the absolute value meets the third threshold range, it indicates that the change trend of the curve is flat, that is, there are images that meet the stability condition in the reference image;
  • the absolute value of the slope change of the fitted curve is also calculated, and if the absolute value of the slope of the fitted curve and the absolute value of the slope change of the fitted curve both meet the threshold range, the change trend of the curve is characterized Flat, that is, there is an image that satisfies the stabilization condition in the reference image.
  • the feature information of the reference image includes one or more of pixel value, definition index, and position information.
  • controller 203 is further configured to:
  • the feature information is position information
  • the adjacent reference images are registered, and the difference in position information between the adjacent reference images is calculated. If the difference meets the threshold range, the reference There is an image satisfying the stabilization condition in the image;
  • the acquiring the characterizing information of the second location, and the characterizing information of the second location determining the first waiting time includes:
  • the first waiting time is determined according to the change of the characterization information of the second position.
  • the image analysis device further includes: a vibration detection sensor; the acquiring characterization information of the second position, and determining the first waiting time according to the characterization information of the second position, includes:
  • the vibration data of the sample to be tested in the second position or the imaging device is acquired by the vibration detection sensor , Using the vibration data as the characterizing information of the second position;
  • the first waiting time is determined according to the change of the characterization information of the second position.
  • controller 203 is further configured to:
  • Output prompt information and/or control the imaging device to acquire an image of the target in the sample to be tested as the target image of the target.
  • the imaging device acquires an image of a target in the sample to be tested, and the target image as the target includes:
  • An image that meets the stabilization condition in the reference image is selected as the target image of the target object.
  • the imaging device acquires an image of a target in the sample to be tested, and the target image as the target includes:
  • the sample to be tested stays at the second position for the first waiting time
  • the first waiting time is from the moment when the sample to be tested moves to the second position or the moment when the imaging device moves to the second position until the target image of the target is acquired The interval between the moments.
  • controller 203 is further configured to:
  • the imaging device After moving the sample to be tested to the second position or the imaging device to the second position, and after a second waiting period has elapsed, the imaging device photographs the target in the sample to be tested at the second position The image is used as a reference image.
  • the sample to be tested is a blood smear
  • the image analysis device is an automated film reader
  • the embodiment of the present invention also provides an image analysis device, which is implemented in the image processing equipment shown in Figs. 2A, 2B, 3 and 4, as shown in Fig. 2A, including:
  • Imaging device 201 mobile device 202, and controller 203;
  • the imaging device 201 includes a camera 2011 and a lens group 2012, and is configured to take an image of a target in the sample to be tested;
  • the moving device 202 has a platform 2021 on which the sample to be tested is placed and a drive unit 2022.
  • the 2012 lens group is located between the camera 2011 and the platform 2021.
  • the drive unit 2022 makes the platform 2021 and the imaging device 201 move relative to each other so that the imaging device 201 can take pictures The target image of the specific area of the sample to be tested;
  • the controller 203 is coupled to the imaging device 201 and the mobile device 202, and is configured to:
  • determining whether there is an image satisfying a stable condition in the reference image based on the feature information of the reference image includes:
  • the judging whether there is an image that satisfies a stable condition in the obtained reference image based on the feature information of at least two reference images includes:
  • the difference of feature information of the adjacent reference images is continuously compared.
  • the judging whether there is an image that satisfies a stable condition in the obtained reference image based on the feature information of at least two reference images includes:
  • the degree of dispersion meets the second threshold range, it indicates that there is an image that satisfies the stabilization condition in the reference image.
  • the judging whether there is an image that satisfies a stable condition in the obtained reference image based on the feature information of at least two reference images includes:
  • a fitting curve is obtained based on the characteristic information of the reference image, and the absolute value of the slope of the fitting curve is calculated; the absolute value of the slope of the fitting curve is compared with a third threshold range; if the slope of the fitting curve is If the absolute value meets the third threshold range, it indicates that there is an image that meets the stabilization condition in the reference image;
  • the absolute value of the slope change of the fitting curve is also calculated, and if the absolute value of the slope of the fitting curve and the absolute value of the slope change of the fitting curve both meet the threshold range, it indicates that there is An image that satisfies the stabilization condition.
  • the feature information of the reference image includes one or more of pixel value, definition index, and position information.
  • the acquiring the image of the target in the sample to be tested at the second position as the target image of the target includes:
  • An image that meets the stabilization condition in the reference image is selected as the target image of the target object.
  • acquiring the image of the target in the sample to be tested at the second position as the target image of the target includes:
  • the imaging device is controlled to take an image of the target in the sample to be tested as the target image of the target.
  • controller 203 is further configured to:
  • the imaging device After moving the sample to be tested to the second position or the imaging device to the second position, and after a second waiting period has elapsed, the imaging device photographs the target in the sample to be tested at the second position The image is used as a reference image.
  • the sample to be tested is a blood smear
  • the image analysis device is an automated film reader
  • the controller in the image analysis device provided by the embodiment of the present invention may be configured to execute the steps of the imaging method of the image analysis device shown in FIG. 6 or FIG. 21.
  • the embodiment of the present invention further provides a storage medium, that is, a computer-readable storage medium, and an executable program is stored on the storage medium.
  • a storage medium that is, a computer-readable storage medium
  • an executable program is stored on the storage medium.
  • the controller may be a CPU, GPU, or other chips with computing capabilities.
  • the memory is loaded with various computer programs for the controller to execute, such as operating system and application programs, and data required to execute the computer programs.
  • various computer programs for the controller to execute such as operating system and application programs, and data required to execute the computer programs.
  • any data that needs to be stored locally can be stored in the memory.
  • the imaging method of the image analysis device is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer readable storage medium.
  • the computer software product is stored in a storage medium and includes several instructions for A computer device (which may be a personal computer, a server, or a network device, etc.) executes all or part of the methods described in the various embodiments of the present invention.
  • the aforementioned storage media include: U disk, mobile hard disk, Read Only Memory (ROM, Read Only Memory), magnetic disk or optical disk and other media that can store program codes. In this way, the embodiments of the present invention are not limited to any specific combination of hardware and software.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are merely illustrative.
  • the division of the units is only a logical function division, and there may be other divisions in actual implementation, such as: multiple units or components can be combined, or It can be integrated into another system, or some features can be ignored or not implemented.
  • the coupling, or direct coupling, or communication connection between the components shown or discussed may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms. of.
  • the units described above as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • the functional units in the embodiments of the present invention can be all integrated into one processing unit, or each unit can be individually used as a unit, or two or more units can be integrated into one unit; the above-mentioned integration
  • the unit can be implemented in the form of hardware, or in the form of hardware plus software functional units.
  • the foregoing program can be stored in a computer readable storage medium.
  • the execution includes The steps of the foregoing method embodiment; and the foregoing storage medium includes: various media that can store program codes, such as a mobile storage device, a read only memory (Read Only Memory, ROM), a magnetic disk, or an optical disk.
  • ROM Read Only Memory
  • the aforementioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it may also be stored in a computer readable storage medium.
  • the computer software product is stored in a storage medium and includes several instructions for A computer device (which may be a personal computer, a server, or a network device, etc.) executes all or part of the methods described in the various embodiments of the present invention.
  • the aforementioned storage media include: removable storage devices, ROMs, magnetic disks or optical discs and other media that can store program codes.

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Abstract

一种图像分析设备成像方法和图像分析装置，所述图像分析设备包括成像装置，所述方法包括：提供待测样本（601）；驱动待测样本从第一位置移动到第二位置，或成像装置第一位置移动到所述第二位置，其中所述第二位置为所述待测样本中目标物位于所述成像装置拍摄范围内的位置（602）；获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长（603）；待测样本在所述第二位置停留所述第一等待时长后，成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像（604）。

Description

一种图像分析装置及其成像方法 技术领域
本发明实施例涉及体外诊断技术，涉及但不限于一种图像分析装置及其成像方法。
背景技术
图像分析设备对血液样本进行细胞图像检测时，将玻片从上一个拍摄位置移动到目标拍摄位置，需要等待一定时间后，在目标拍摄位置对血液细胞进行拍摄。
这里，由于机械装置运动结束到机械装置彻底静止需要一段时间，在这段时间内，机械装置实际上在持续抖动，抖动的幅度可能多达数微米。而对于具有一定放大倍数的高倍镜，比如：100倍的高倍镜来说，如果在这个抖动过程中就开始自动对焦或者直接进行拍摄，拍摄的图像将会出现由抖动造成的模糊。因此，通过等待一段时长T，能够尽量避免抖动模糊。
相关技术中，在同一高倍镜拍摄过程中，每次移动后等待时长T的大小是设置的固定值，使得拍摄过程存在以下情况：在机械装置抖动还不满足拍摄条件下开始拍摄待分析的目标图像，或在还未等待时长T时，机械装置已经停止抖动，但图像分析设备仍然会在等待时长T后再开始拍摄待分析的目标图像。因此，上述方案会要么存在拍摄的细胞图像模糊不清，要么存在浪费时间资源的情况，导致图像分析设备的工作效率低。
发明内容
本发明实施例提供了一种图像分析装置及其成像方法，能够动态调节开始拍摄待分析的目标图像之前的等待时间，在保证拍摄的图像清晰的情况下，提高时间资源的利用率。
一方面，本发明实施例提供一种图像分析设备成像方法，所述图像分 析设备包括成像装置，所述方法包括：
提供待测样本；
驱动待测样本从第一位置移动到第二位置，或成像装置第一位置移动到所述第二位置，其中所述第二位置为所述待测样本中目标物位于所述成像装置拍摄范围内的位置；获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长；待测样本在所述第二位置停留所述第一等待时长后，通过所述成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像。
一方面，本发明实施例提供一种图像分析设备成像方法，所述分析设备包括成像装置，所述方法包括：
提供待测样本；
驱动待测样本从第一位置移动到第二位置或所述成像装置从第一位置移动到所述第二位置，其中所述第二位置为所述待测样本中目标物位于所述成像装置拍摄范围内的位置；
所述成像装置拍摄至少两张位于所述第二位置的所述待测样本中目标物的图像，作为目标物的参考图像；
基于所述参考图像的特征信息，判断所述参考图像中是否存在满足稳定条件的图像；
当所述图像中未出现满足条件的图像时，所述成像装置继续拍摄位于所述第二位置的所述待测样本中目标物的图像，作为目标物的参考图像；
当所述图像中出现满足稳定条件的图像时，获取位于所述第二位置的所述待测样本中目标物的图像，作为目标物的目标图像。
一方面，本发明实施例提供一种图像分析装置，所述装置包括：
成像装置、移动装置和控制器；
所述成像装置包括相机和透镜组，配置为拍摄待测样本中目标物的图 像；
所述移动装置，具有放置所述待测样本的平台和驱动部，所述透镜组位于所述相机和所述平台之间，所述驱动部使所述平台和成像装置进行相对运动，以便成像装置拍摄所述待测样本的特定区域的目标物图像；
所述控制器，与所述成像装置和移动装置耦联，并配置为：
控制待测样本与成像装置从第一位置相对移动到第二位置，其中，在所述第二位置，所述待测样本中目标物位于所述成像装置的拍摄范围内；获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长；所述待测样本在第二位置停留所述第一等待时长后，获取所述待测样本中的目标物图像，作为所述目标物的目标图像。
一方面，本发明实施例提供一种图像分析装置，所述装置包括：
成像装置、移动装置和控制器；
所述成像装置包括相机和透镜组，配置为拍摄待测样本中目标物的图像；
所述移动装置，具有放置所述待测样本的平台和驱动部，所述透镜组位于所述相机和所述平台之间，所述驱动部使所述平台和成像装置进行相对运动，以便成像装置拍摄所述待测样本的特定区域的目标物图像；
所述控制器，与所述成像装置和所述移动装置耦联，并配置为：
控制所述待测样本与成像装置从第一位置相对移动到第二位置，在所述第二位置，待测样本中的目标物位于所述成像装置的拍摄范围内，并控制所述成像装置拍摄至少两张所述第二位置的所述待测样本中的目标物的图像，作为目标物的参考图像；基于所述参考图像中的特征信息，判断所述参考图像中是否存在满足稳定条件的图像；当所述图像中出现满足稳定条件的图像时，获取位于所述第二位置的所述待测样本中目标物的图像，作为目标物的目标图像；当所述图像中未出现满足条件的图像时，控制所 述成像装置在所述第二位置继续拍摄参考图像。
本发明实施例提供一种存储介质，所述存储介质上存储有计算机程序，所述计算机程序被控制器执行时，实现上述图像分析装置执行的图像分析设备成像方法的步骤。
本发明实施例中，当待测样本从第一位置移动到第二位置或成像装置从第一位置移动到第二位置，在获取位于第二位置的待分析的待测样本中目标物的图像之前，停留所述第一等待时长后，通过所述成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像，且第一等待时长由第二位置的表征信息决定，使得等待的时间与移动的位置相适应，在保证拍摄的图像清晰的情况下，提高时间资源的利用率，提高图像分析设备的工作效率。
附图说明
图1为本发明实施例提供的细胞图像示意图；
图2A为本发明实施例提供的图像分析设备的可选的结构示意图；
图2B为本发明实施例提供的图像分析设备的可选的结构示意图；
图3为本发明实施例提供的图像分析设备的可选的结构示意图；
图4为本发明实施例提供的图像分析设备的可选的结构示意图；
图5为本发明实施例提供的样本分析系统的可选的结构示意图；
图6为本发明实施例提供的图像分析设备成像方法的可选地流程示意图；
图7为本发明实施例提供的待测样本和成像装置相对运动示意图；
图8A为本发明实施例提供的图像分析设备成像方法的可选地流程示意图；
图8B为本发明实施例提供的图像分析设备成像方法的可选地流程示意图；
图9为本发明实施例提供的参考图像示意图；
图10为本发明实施例提供的确定满足稳定条件的图像的可选地示意图；
图11A为本发明实施例提供的确定满足稳定条件的图像的可选地示意图；
图11B为本发明实施例提供的确定满足稳定条件的图像的可选地示意图；
图12为本发明实施例提供的配准示意图；
图13为本发明实施例提供的确定满足稳定条件的图像的可选地示意图；
图14为本发明实施例提供的拟合曲线的可选地曲线示意图；
图15为本发明实施例提供的拟合曲线的可选地曲线示意图；
图16为本发明实施例提供的拟合曲线的可选地曲线示意图；
图17为本发明实施例提供的拟合曲线的可选地曲线示意图；
图18为本发明实施例提供的图像分析设备成像方法的可选地流程示意图；
图19为本发明实施例提供的图像分析设备成像方法的可选地流程示意图；
图20为本发明实施例提供的图像分析设备成像方法的可选地流程示意图；
图21为本发明实施例提供的图像分析设备成像方法的可选地流程示意图；
图22为本发明实施例提供的图像分析设备成像方法的可选地流程示意图；
图23为本发明实施例提供的图像分析设备成像方法的可选地流程示意 图；
图24为本发明实施例提供的图像分析设备成像方法的可选地流程示意图；
图25为本发明实施例提供的图像分析设备成像方法的可选地流程示意图。
具体实施方式
以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所提供的实施例仅仅用以解释本发明，并不用于限定本发明。另外，以下所提供的实施例是用于实施本发明的部分实施例，而非提供实施本发明的全部实施例，在不冲突的情况下，本发明实施例记载的技术方案可以任意组合的方式实施。
相关技术中，通过图像分析设备拍摄血液细胞图像的流程包括：使用低倍镜(例如：10倍)定位血涂片中的白细胞，然后使用高倍镜(例如：100倍)对低倍镜定位到的白细胞进行逐个拍摄。
在拍摄过程中，上一拍摄的位置为A(X1，Y1)，当前需拍摄的位置为B(X2，Y2)，图像分析设备通过控制成像装置或玻片的移动，将拍摄位置从A位置移动到B位置。由于图像分析设备的成像装置或玻片的机械运动导致图像分析设备中整体或部分组件在一段时间内存在抖动，抖动的幅度可达数微米。而通过高倍镜(例如：100倍)拍摄细胞图像时，拍摄的景深较小，图像分析设备的抖动能够造成拍摄的细胞图像出现模糊不清的情况，如图1所示。因此，为了避免拍摄的细胞图像模糊不清，当图像分析设备移动到B位置后，需要等待一段时间T后开始再进行拍摄。
这里，不同白细胞之间的间隔不同，玻片或成像装置移动距离也就不同，所需的等待时长也会不相同。但为了使所有的白细胞都能被清晰的拍摄，等待时长T会取能清晰拍摄所有白细胞中等待时长的最大值，比如： 移动拍摄各个白细胞的间隔中最大间隔对应的时间。也就是说，不管A位置与B位置的距离是多少，等待的时长T是相同的。比如：若A位置与B位置之间的间隔小于最大间隔，即使在图像分析设备已经稳定不抖动的情况下，图像分析设备仍然在等待，直到等待的时长为T，才会去拍摄待分析的目标图像，这会造成时间上的浪费，降低图像分析设备的工作效率，进而不能满足用户的需要。
基于上述技术问题，提供一种图像分析设备成像方法，所述图像分析设备包括成像装置，所述方法包括：提供待测样本；驱动待测样本从第一位置移动到第二位置，或成像装置第一位置移动到所述第二位置，其中所述第二位置为所述待测样本中目标物位于所述成像装置拍摄范围内的位置；获取第二位置的表征信息，根据第二位置的表征信息决定第一等待时长；待测样本在所述第二位置停留所述第一等待时长后，成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像。所述方法中所述第一等待时长由不同第二位置的表征信息动态决定，也即决定成像装置何时获取所述目标物的目标图像。其中，所述第一等待时长不是固定值，是根据不同第二位置的表征信息不断变化的。所述方法在能保证拍摄的图像清晰的情况下，提高时间资源的利用率，进而提高图像分析设备的工作效率。
所述图像分析设备用于对待测样本中目标物进行图像拍摄和分析，得到阅片结果。所述图像分析设备可为自动化阅片机。
其中，待测样本可包括：血涂片、骨髓涂片、病理切片、含细菌的样本涂片、尿沉渣样本等，还可为其他体液的涂片。当待测样本为血涂片，目标物可为血细胞，如白细胞；当待测样本为骨髓涂片，目标物可为骨髓细胞；当待测样本为病理切片，目标物可为某种病变组织；当待测样本为含细菌的样本涂片，目标物可为细菌；当待测样本为尿沉渣样本时，可以 不制作成涂片，比如：可使尿液沉积在容器中形成尿沉渣的样本，目标物为尿液中的某种沉渣物。本发明实施例中，对待测样本的类型，以及相应的目标物，不进行任何的限定。
如图2A所示，图像分析设备200包括：成像装置201、移动装置202和控制器203，其中，成像装置201包括相机2011和透镜组2012，移动装置202包括放置待测样本的平台2021和驱动部2022。
成像装置201用于拍摄待测样本中目标物的图像；
移动装置202用于使待测样本相对于成像装置201进行运动，以便成像装置201拍摄待测样本的特定区域的目标物的图像；
控制器203，用于对图像分析设备200中成像装置和移动装置进行控制，并对图像分析设备200中的数据进行处理。
在一示例中，如图2B所示，图像分析设备200还包括：振动检测传感器208，能够检测图像分析设备200或某些其部件的机械运动，并将检测机械量转换为电量数据。
以下为方便描述，以待测样本为血涂片为例对本发明实施例提供的图像分析设备作进一步描述，以下描述同样适用于其他待测样本。当待测样本为血涂片，成像装置用于拍摄血涂片的特定区域的细胞图像。
在一示例中，如图3所示，图像分析设备200还包括：识别装置204、玻片夹取装置205和玻片回收装置206。识别装置204用于识别涂片的身份信息，玻片夹取装置205用于将涂片从识别装置204夹取到移动装置202上进行检测，玻片回收装置206用于放置经检测的涂片。
图像分析设备200还包括玻片篮装载装置207，用于装载装有待测涂片的玻片篮，玻片夹取装置205还用于将玻片篮装载装置207上装载的玻片篮中的待测涂片夹取到识别装置204进行身份信息识别。
在一示例中，如图4所示，透镜组可以包括第一物镜401和第二物镜 402。第一物镜401例如可以为10倍物镜，第二物镜402例如可以为100倍物镜。透镜组还可以包括第三物镜403，第三物镜403例如可以为40倍物镜。其中，透镜组还可以包括目镜。
移动装置202用于使涂片21相对于相机2011运动，以便相机2011拍摄涂片21的特定区域的细胞图像。其中，未被拍摄的制备好的涂片21装载在玻片篮20上。
在一实施例中，血涂片中的细胞可包括白细胞、红细胞和血小板等，其可以通过将动物或人身上抽取的全血经过稀释液、溶血剂等处理后而获得。其中，白细胞的分类可包括三分类、四分类和五分类。以三分类为例，是指将白细胞分成三大类，是通过一定的稀释液将分别为小细胞群(由淋巴细胞(Lymphocyte，Lyn)构成的细胞群)、中间细胞群(由单核细胞(Monocyte，Mon)构成的细胞群)和大细胞群(由粒细胞(Granulocyte)构成的细群)，并得到血样中的淋巴细胞、单核细胞和粒细胞的数量。五分类可以借助一定的稀释及化学染色或者阻抗法的方法将白细胞直接分为中性粒细胞(neutrophil，Neu)、淋巴细胞(Lyn)、嗜酸性粒细胞(eosinophilia，Eos)、嗜碱性粒细胞(basoophilicgranulocyte，Bas或Baso)、单核细胞(Mon)。
图像分析设备200的阅片结果包括：分析信息、白细胞、红细胞和血小板。其中，白细胞对应的检测结果包括以下细胞的细胞图像：中性分叶核粒细胞、中性杆状核粒细胞、淋巴细胞、单核细胞、嗜酸性粒细胞、嗜碱性粒细胞、中性中幼粒细胞、中性晚幼粒细胞、早幼粒细胞、原始细胞、异性淋巴细胞、浆细胞等。
在一示例中，当待测样本为血涂片，本发明实施例提供的图像分析设备200可应用于图5所示的样本分析系统500中，如图5所示，样本分析系统500包括血液分析仪501、涂片制备装置502、图像分析设备200和控制装置504。
血液分析仪501用于对待测血涂片进行血常规检测，得到血常规结果。涂片制备装置502用于制备待测血涂片的涂片。图像分析设备200用于对涂片中的细胞进行图像拍摄和分析，得到阅片结果。控制装置504与血液分析仪501、涂片制备装置502和图像分析设备200通信连接，收集图像分析设备200的阅片结果和血液分析仪501的血常规结果，并对收集的阅片结果和血常规结果进行处理。
样本分析系统500还包括第一传输轨道505和第二传输轨道506，第一传输轨道505用于将可放置多个装载有待测血样的试管11的试管架10从血液分析仪501运送至涂片制备装置502，第二传输轨道505用于将可装载多个制备好的涂片21的玻片篮20从涂片制备装置502运送至图像分析设备200。
控制装置504与第一传输轨道505和第二传输轨道506电连接并控制其动作。
样本分析系统500还包括分别对应于血液分析仪501和涂片制备装置502设置的进给机构507和508，各进给机构507和508包括装载缓存区171和181、进给检测区172和183以及卸载缓存区173和183。
当试管架10上的待测血涂片需要被运送至血液分析仪501进行检测时，试管架10首先从第一传输轨道505被运送到装载缓存区171，然后从装载缓存区171被运送到进给检测区172由血液分析仪501进行检测，在检测结束之后，再从进给检测区172被卸载到卸载缓存区173，最后再从卸载缓存区173进入第一传输轨道505。
同理，当试管架10上的待测血涂片需要进行镜检时，需要将试管架10运送至涂片制备装置502制备涂片，试管架10首先从第一传输轨道505被运送到装载缓存区181，然后从装载缓存区181被运送到进给检测区182由涂片制备装置502制备涂片，在涂片制备结束之后，再从进给检测区182 被卸载到卸载缓存区183，最后再从卸载缓存区183进入第一传输轨道505。涂片制备装置502将制备好的涂片21收纳在玻片篮20中，通过第二传输轨道506将收纳有待测涂片21的玻片篮20运送至图像分析设备200，图像分析设备200对待测涂片21上的血涂片中的细胞进行图像拍摄并进行分析。
这里，涂片制备装置502在制备涂片的过程中，可从试管架上的试管的标签上得到试管中装置的血涂片的样本信息，并将携带有样本信息的条形码、二维码等信息标识喷涂在涂片上。
当然，本发明实施例不局限于提供为方法和硬件，还可有多种实现方式，例如提供存储介质(存储有用于执行本发明实施例提供的成像方法的程序或指令)。
如图6所示实施例提供一种图像分析设备成像方法的流程示意图，包括：
S601：提供待测样本；
其中，待测样本可为血涂片，血涂片由待测血液样品制备得到。
S602：驱动待测样本从第一位置移动到第二位置，或成像装置第一位置移动到所述第二位置，其中所述第二位置为所述待测样本中目标物位于所述成像装置拍摄范围内的位置；
其中，待测样本可为血涂片，目标物可为血涂片中任一种或多种细胞，如白细胞、红细胞和/或血小板。
如图7所示，成像装置对准的第一个拍摄位置为位置A，通过移动成像装置或待测样本，使得成像装置对准的第二个拍摄位置为位置B。这里，位置A可称为第一位置，位置B可称为第二位置。其中，成像装置在第一位置和第二位置进行成像时，可使用同一个物镜。例如：在高倍镜下，对血涂片中不同位置的白细胞进行逐个拍摄的过程中，不更换高倍镜，采用 同一高倍镜完成所述拍摄过程。这里，移动成像装置或待测样本的方向可包括X方向、Y方向和Z方向中的一个或多个的组合。
S603：获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长；
该步骤中，获取的不同第二位置的表征信息不同的情况下，根据所述特征信息相应确定的第一等待时长也可能不同。不同第二位置的对应第一等待时长不是固定的值，是随着获取的第二位置特征信息动态变化的，即可根据移动位置的实际情况，动态确定第一等待时长。
例如：待测样本为血涂片，当血涂片从位置a1移动到位置a2进行拍摄，第一等待时长为ΔT1，当血涂片从位置a2移动到位置a3进行拍摄，第一等待时长为ΔT2，当血涂片从位置a3移动到位置a4进行拍摄，第一等待时长为ΔT3……，且ΔT1、ΔT2、ΔT3可能相同，也可能不同，是根据实际移动情况动态变化的，并非固定值。
S604：待测样本在所述第二位置停留所述第一等待时长后，成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像。
其中，待测样本在所述第二位置停留所述第一等待时长，可使图像分析设备逐渐稳定，即图像分析设备不再抖动，或抖动的程度很小，但此时获取的目标物的目标图像质量已经能满足需要。故在第一等待时长后，可获取清晰的所述目标物的目标图像。
图像分析设备的抖动可包括：基于待测样本或成像装置的移动而产生的图像分析设备整体的抖动，或者某些部件的抖动，例如：移动部件的抖动，可为：待测样本的抖动、或成像装置的抖动等。
因此，上述方法在能保证获取的目标物的目标图像清晰的情况下，提高时间资源的利用率，提高图像分析设备的工作效率。
上述S603：获取第二位置的表征信息，所述第二位置的表征信息决定 第一等待时长；
如图8A所示，包括以下步骤：
S6031A：所述待测样本或所述成像装置移动到所述第二位置，所述成像装置拍摄至少两张所述待测样本中目标物的参考图像，所述参考图像的特征信息作为第二位置的表征信息；
其中，所述特征信息包括：像素值、清晰度指标和位置信息中的一种或多种。成像装置可在待测样本或所述成像装置移动到第二位置时，立即开始拍摄所述参考图像；也可在待测样本或所述成像装置移动到第二位置，并经过第二等待时长后，开始拍摄所述参考图像。
所述第二等待时长为所述待测样本移动到所述第二位置的时刻或所述成像装置移动到所述第二位置的时刻至获取所述待测样本中目标物的参考图像的时刻之间的间隔。
所述第一等待时长为所述待测样本移动到所述第二位置的时刻或所述成像装置移动到所述第二位置的时刻至获取所述待测样本中目标物的目标图像的时刻之间的间隔；
可见，所述第一等待时长包括所述第二等待时长。
图像分析设备可周期性地拍摄参考图像，可以边拍摄参考图像，边判断图像分析设备抖动情况，确定第一等待时长。其中，图像分析设备可基于帧率周期性地拍摄参考图像，此时，拍摄参考图像的周期T 拍＝1/帧率。
S6032A：根据所述第二位置的表征信息的变化，确定所述第一等待时长。
其中，根据所述参考图像的特征信息的变化，确定所述第一等待时长，即通过参考图像的特征信息的变化，判断图像分析设备何时会稳定，不再发生抖动，进而得到获取所述目标物的目标图像的时机。
上述S6032A，如图8B所示，还可包括以下步骤：
S6032A1：基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像；
S6032A2：如果存在满足所述稳定条件的图像，则确定所述第一等待时长；
S6032A3：如果不存在满足所述稳定条件的图像，则继续拍摄参考图像。
一个实施例中，当拍摄的所述参考图像中一张或连续多张图像满足所述稳定条件时，确定所述第一等待时长。其中，所述连续多张图像为连续拍摄得到的多张图像，可至少为3张，也可为4张，5张，6张，8张等。
例如：获取参考图像包括：图像1、图像2、图像3……图像35，当图像35满足稳定条件，则表征图像分析设备已经稳定不再抖动，图像分析设备停止参考图像的拍摄，且获取目标物的目标图像。当图像35未满足稳定条件，则继续拍摄新的参考图像，并基于新的参考图像继续判断图像分析设备的抖动情况。
例如：获取参考图像包括：连续拍摄得到的图像1、图像2、图像3……图像35，若当前连续拍摄获得的几张最新参考图像如：图像33、图像34、图像35均满足稳定条件时，即可确定第一等待时长，也表征图像分析设备已经稳定不再抖动，图像分析设备停止参考图像的拍摄，且获取目标物的目标图像。当未满足上述稳定条件，则继续拍摄新的参考图像，并基于新的参考图像判断图像分析设备的抖动情况。
上述S6032A1：所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
1)基于至少两个所述参考图像的特征信息的差异；
2)如所述差异符合第一阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
一个实施例中，连续比较相邻的所述参考图像的特征信息的差异。
其中，若连续多张参考图像对应的特征信息差异均符合第一阈值范围，则表征有连续多张参考图像满足稳定条件，更能表明设备目前已经稳定，可以清晰的获取所述目标物的目标图像。
一个实施例中，比较相邻两个所述参考图像的特征信息，获得所述参考图像对应的特征信息差，如像素差、位置信息差等；将所述参考图像对应的特征信息差与第一阈值进行比较；若存在所述特征信息差小于第一阈值的情况，则表征所述参考图像中存在满足所述稳定条件的图像。其中，所述特征信息差可取绝对值。
另一实施例中，若连续多张所述参考图像对应的特征信息差均小于第一阈值，则认为分析设备已经稳定，可获取目标物的目标图像。其中，所述特征信息差可取绝对值。
比如：获取的参考图像包括：图像1、图像2、图像3、图像4、图像5……，图像1和图像2的特征信息之间的差(其中，所述特征信息差可取绝对值)，得到图像2对应的特征信息差；计算图像2和图像3的特征信息之间的差，得到图像3对应的特征信息差……，以此类推计算，即不断计算当前获取的最新图像与上一张图像的差。当图像10对应的特征信息差的小于第一阈值，或图像8、图像9和图像10对应的特征信息差均小于第一阈值，则认为设备不再抖动，已经稳定，故停止参考图像的获取，并停止特征信息差的计算，获取目标物的目标图像。
在一示例中，将参考图像中的一图像作为对比图像，将对比图像之后的参考图像分别和对比图像的特征信息进行比较，得到各参考图像对应的特征信息差(其中，所述特征信息差可取绝对值)。对比图像可为参考图像中任一图像。比如：参考图像集合中的参考图像包括：图像1、图像2、图像3、图像4、图像5……，对比图像为图像1，计算图像1和图像2的特 征信息之间的差，即差1；计算图像1和图像3的特征信息之间的差，即差2，将差1和差2比较，得到图像3对应的特征信息差；计算图像1和图像4的特征信息之间的差，即差3，将差2和差3进行比较，得到图像3对应的特征信息差……，以此类推。当图像10对应的特征信息差的小于第一阈值，或图像8、图像9和图像10对应的特征信息差均小于第一阈值，则停止参考图像的拍摄，并停止特征信息差的计算，获取目标物的目标图像。
一个实施例中，参考图像的特征信息可为像素值、清晰度指标和位置信息中的一种或多种。
一个实施例中，参考图像的特征信息为像素值；可计算两张参考图像之间的像素差，如图9所示，参考图像包括图像901和图像902，基于图像901中区域Q1中各个像素的值得到图像901的像素值，即区域Q1对应的像素矩阵1。基于图像902中区域Q2中各个像素值得到图像902的像素值，即区域Q2对应的像素矩阵2。其中，像素矩阵1为
Figure PCTCN2020115420-appb-000001
像素矩阵2为
Figure PCTCN2020115420-appb-000002
对像素矩阵1和像素矩阵2做差，得到差值矩阵：
Figure PCTCN2020115420-appb-000003
基于差值矩阵得到两者的像素差：0.005。
另一实施例中，计算两幅图像的像素差可以基于图像中部分区域或全部区域进行比较计算得到。
以参考图像的特征信息为像素值为例，如图10所示，参考图像包括：图像1001、图像1002、图像1003、图像1004……，其中，计算相邻的两张图像1001和图像1002之间的像素差1，作为图像1002对应的像素差；计算相邻的两张图像1002和图像1003之间的像素差2，作为图像1003对应的像素差；计算相邻的两张图像1003和图像1004之间的像素差3，作为图像1004对应的像素差，以此类推，即可得到当前拍摄的各参考图像对应的像素差。若当前获得的最新参考图像对应的像素差(可取绝对值)小于阈值，或最新获得的连续几张参考图像对应的像素差均小于阈值，则可认为设备已经稳定，抖动已经停止。如图10中，时间窗W1(可以当前时刻为起点向前选择一段时间)，若时间窗W1中所有图像对应的像素差均小于阈值，则确定时间窗W1中对应的各参考图像均为满足稳定条件的图像。若时间窗内有图像对应的像素差大于阈值，则继续拍摄参考图像计算其对应的像素差，相应的沿时间轴滑动时间窗并重新进行上述判断。所述时间窗可以根据需要设置为固定值。
以参考图像的特征信息为位置信息为例，特征信息差为位置差，如平移量。其中，平移量可为X轴平移量和Y轴平移量中的一种或两种的组合。
在一实施例中，提取图像中保持不变特征，即分别提取两幅图像中共有图像内容的特征，称为目标特征。确定共有的目标特征在两张图像中的位置信息，将所述两个位置信息进行比较，得到两张参考图像之间的平移量，如平移量符合平移量阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；其中，所述两张参考图像可为相邻的两张参考图像。
其中，所提取目标特征是出现在两幅图像中对比例、旋转、平移等变换保持一致性的特征，如线交叉点、物体边缘角点、虚圆闭区域的中心等可提取的特征。特征包括：点、线和面三类，如白细胞的边缘等。特征提取方法可包括：Harris(Harris Corner Detector)算法、Susan(Susan Corner  Detector)算法、SIFT特征点提取、SURF特征点提取、FAST(Features from Accelerated Segment Test)点特征提取、Robert线特征提取、Mser面特征提取等方法。本实施例对特征提取方法不进行任何的限定。
一个实施例中，如图11A所示，获得的参考图像包括：图像1101、图像1102、图像1103、图像1104……，其中，提取图像中共有的细胞C1的特征，确定细胞C1在相邻两张图像1101中的位置信息和在图像1102中的位置信息之间位置差，也为X轴的平移量1，作为图像1102对应的平移量。细胞C1在相邻两张图像1102中的位置信息和在图像1103中的位置信息之间的位置差，也为X轴的平移量2，作为图像1103对应的平移量。细胞C1在相邻两张图像1103中的位置信息和在图像1104中的位置信息之间的位置差，也为X轴的平移量3，作为图像1104对应的平移量，以此类推，得到各参考图像对应的平移量。
若当前获得的最新参考图像对应的X轴的平移量(可取绝对值)小于阈值，或最新获得的连续几张参考图像对应的X轴的平移量均小于阈值，则可认为设备已经稳定，抖动已经停止。
如图11A，时间窗W2(以当前时刻为起点向前选择一段时间)，若时间窗W2中所有图像对应的X轴的平移量均小于X轴平移量阈值，则确定时间窗W2中对应的各参考图像均为满足稳定条件的图像。若时间窗内有图像对应的X轴的平移量大于X轴平移量阈值，则继续拍摄参考图像计算其对应的X轴的平移量，相应的沿时间轴滑动时间窗并重新进行上述判断。所述时间窗可以根据需要设置为固定值。
一个实施例中，如图11B所示，参考图像包括：图像1101、图像1102、图像1103、图像1104……，其中，提取图像中共有的C1特征，确定细胞C1在相邻两张图像1101中的位置信息和在图像1102中的位置信息之间的Y轴的平移量1，作为图像1102对应的平移量。确定细胞C1在相邻两张图 像1102中的位置信息和在图像1103中的位置信息之间的Y轴的平移量2，作为图像1102对应的平移量。确定细胞C1在相邻两张图像1103中的位置信息和在图像1104中的位置信息之间的Y轴的平移量3，以此类推，得到当前拍摄的所有参考图像对应的平移量。
若当前获得的最新参考图像对应的Y轴的平移量(可取绝对值)小于阈值，或最新获得的连续几张参考图像对应的Y轴的平移量均小于Y轴平移量阈值，则可认为设备已经稳定，抖动已经停止。
如图11B，时间窗W3(以当前时刻为起点向前选择一段时间)，若时间窗W3中所有图像对应的Y轴的平移量均小于Y轴平移量阈值，则确定时间窗W3中对应的各参考图像均为满足稳定条件的图像。若时间窗内有图像对应的Y轴的平移量大于Y轴平移量阈值，则继续拍摄参考图像计算其对应的Y轴的平移量，相应的沿时间轴滑动时间窗并重新进行上述判断。所述时间窗W2可以根据需要设置为固定值。
一个实施例中，若当前获得的最新参考图像对应的X轴平移量和Y轴的平移量(可取绝对值)均符合相应的平移量阈值范围，或最新获得的连续几张参考图像对应的X轴和Y轴的平移量均都符合相应的平移量阈值范围，则可认为设备已经稳定，抖动已经停止。其中，图像对应的X轴和Y轴的平移量都满足阈值要求，更能保证分析设备已经稳定，此时可获取目标图像。
在一实施例中，将两张参考图像进行配准，计算得到所述参考图像之间位置信息的差值，如所述差值符合阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。其中，所述两张图像可为相邻的两张图像。
配准方式一、基于灰度的配准，即直接利用至少局部图像的灰度信息建立两幅图像之间的相似性度量，然后采用搜索方法寻找使相似性度量值最大或最小的变换模型的参数值。
配准方式二、基于特征的配准，即提取图像中保持不变特征如边缘点、封闭区域的中心等作为两幅图像配准的参考信息，可参考前文提取所述目标特征的方法，此处不再重复。
基于配准方式一，可通过查找相邻的所述参考图像之间相关的区域；在相邻的所述参考图像基于所述相关的区域重叠的情况下，确定所述相邻参考图像中指定位置之间的位置差。
这里，查找相邻的两个参考图像中相关性最大的位置，并在相关性最大的位置将两个区域重叠的情况下，确定指定点分别在两个参考图像中的位置信息，对两个位置信息进行比较，得到平移量。
在查找相邻的两个参考图像中相关性最大的位置时，可固定一图像，并滑动另一图像，每滑动一个位置，计算两个图像的重叠区域的相关性，并找出相关性最大的位置。
例如，两个图像的重叠区域的相关性γ可通过公式(2)计算：
Figure PCTCN2020115420-appb-000004
其中，f(x，y)与g(x，y)分别为两个重叠的区域中的点(x，y)处分别对应的像素值，
Figure PCTCN2020115420-appb-000005
与
Figure PCTCN2020115420-appb-000006
分别为两个重叠的区域中的所有像素点的像素值的均值。但不局限于上述公式。
如图12所示实施例，相邻的参考图像包括图像1201和图像1202，固定图像1201，在图像1201上滑动图像1202，每滑动一个位置，则计算重叠区域的相关性，当在图像1201上滑动图像1202得到的位置为图12中的(1)所示，图像1201中的区域A1与图像1202中的区域A2重叠，计算区域A1和区域A2的相关性，得到相关性r1。当图像1201上滑动图像1202得到的位置为图12中的(2)所示，得到重叠的区域的相关性，得到相关 性r2。当图像1201上滑动图像1202得到的位置为图12中的(3)所示，得到重叠的区域的相关性，得到相关性r3，依次类推，确定图像1201和图像1202在每一个滑动位置上的重叠区域的相关性。最终找到相关性最大的位置。若如图12中的(3)所示位置得到相关性r3最大，以指定点为图像的左上顶点为例，分别计算图像1201的左上顶点的位置信息和图像1201的左上顶点的位置信息，并对两个位置信息进行比较，得到平移量，可包括X和Y轴的平移量。据此，判断设备是否已经稳定。
上述S6032A1：所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
1)计算连续多张所述参考图像的特征信息和/或特征信息差的离散程度；
2)将所述离散程度与第二阈值范围进行比较；
3)若所述离散程度符合第二阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
其中，离散程度是指各个特征信息或特征信息差之间的差异程度。离散程度可包括极差、平均差和标准差等。本实施例中对离散程度的表征方式不进行任何的限定。其中，特征信息可为像素值、清晰度指标和位置信息中的一种或多种。
如图13所示实施例，以特征信息为清晰度指标，如对焦度，且计算对焦度的离散程度。1301、1302、1303分别为参考图像中第一张图像、第二张图像、第三张图像的对焦度，以此类推，所述曲线为获取的参考图像对焦度随时间的变化图。图13中，时间窗W4(以当前时刻为起点向前选择一段时间)，计算时间窗W4内相应参考图像对焦度的离散程度，判断得到的离散程度是否小于离散程度阈值，若小于则时间窗W4内相应参考图像都满足稳定条件，可认为设备已稳定。若大于或等于所述阈值，则需要重新拍摄参考图像获得其对焦度，反映在图13中需要沿时间轴滑动时间窗 W4，重新计算离散程度进行判断。其中，时间窗W4可根据需要设置固定值。例如：离散程度α可通过公式(3)来表征：
Figure PCTCN2020115420-appb-000007
其中，Imax为时间窗W4中各参考图像的特征信息或对应特征信息差中最大值，Imin时间窗W4中各参考图像的特征信息或对应特征信息差中最小值，I从0时刻到当前窗口的所有参考图像的特征信息或对应特征信息差的平均值。
此外，计算离散程度时，还可直接计算当前获取的连续多张最新图像(即以获取的最新图像为起点向前连续选取几张图像)进行计算。
以计算连续三个像素差的离散程度为例，当最新拍摄的参考图像为图像5，则计算图像3、图像4、图像5对应的像素差的离散程度3，当计算的离散程度3大于离散程度阈值，则继续获取新的参考图像：图像6，并计算图像4、图像5、图像6对应的像素差的离散程度4，当计算的离散程度4大于离散程度阈值，则继续获取新的参考图像,以此类推。当图像10、图像11、图像12对应的像素差的离散程度10小于离散程度阈值，则图像10、图像11、图像12为满足稳定条件的图像，认为设备已经稳定不再抖动，停止参考图像的获取。
其他实施例中，除清晰度指标、像素差外，还可计算位置信息及其差、清晰度指标的差、像素值等的离散程度，方法类似上述实施例，此处不再一一举例。
上述S6032A1：所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
基于所述参考图像的特征信息获得曲线，判断曲线的变化趋势是否平坦。
一个实施例中，基于所述参考图像的特征信息获得曲线，判断曲线的 变化趋势是否平坦，包括以下步骤：
基于所述参考图像的特征信息获得拟合曲线，计算所述拟合曲线斜率的绝对值；将所述拟合曲线斜率的绝对值与第三阈值范围进行比较；若所述拟合曲线斜率的绝对值符合所述第三阈值范围，则表征所述曲线的变化趋势平坦，即所述参考图像中存在满足所述稳定条件的图像，可认为分析设备已经稳定。
优选的，还计算所述拟合曲线斜率变化的绝对值，如果所述拟合曲线斜率的绝对值和所述拟合曲线斜率变化的绝对值均符合阈值范围，则表征所述曲线的变化趋势平坦，即所述参考图像中存在满足所述稳定条件的图像。能够更精确地判断出图像分析设备是否稳定。
其中，拟合曲线的斜率可为拟合曲线的一阶导，拟合曲线的斜率变化可为拟合曲线的二阶导。
如图14所示实施例，绘制获得的各参考图像的特征信息随时间变化的曲线，取曲线上方的点拟合包络线L1，也可以当前时间为起点选取之前一段时间内特征信息随时间变化的曲线拟合包络线。包络线的方程m＝s(n)，n是时间，m是曲线的值，计算s(n)的一阶导s′和二阶导s″，其中，当一阶导越大，表示曲线下降坡度越大；二阶导越大，表示曲线的斜率变化越大。当一阶导和二阶导满足下列条件时，表明拟合曲线趋于平稳：s′＜S1且s″＜S2，其中，S1和S2可为设定的经验值。
一个实施例中，拟合曲线可基于当前获取参考图像所有特征信息的包络线，也可基于部分特征信息的包络线。
一个实施例中，以最新拍摄的参考图像的特征信息为起点，选取连续多个参考图像的特征信息做拟合，得到拟合曲线。例如：选取数量为3，当最新获取的图像为图像3，则将图像1、图像2和图像3的特征信息做拟合，得到拟合曲线1，计算拟合曲线上最后一个点或连续多个点的斜率，来判断 最新获取的图像是否满足稳定条件。若不满足，继续获取新的参考图像4，再将图像2、图像3和图像4的特征信息做拟合，得到拟合曲线2，再计算拟合曲线上最后一个点或连续多个点的斜率，来判断最新获取的图像是否满足稳定条件，若斜率小于相应阈值，则认为图像2、图像3和图像4为满足稳定条件的图像，表明分析设备已经稳定，不再获取新的参考图像。
一个实施例中，拟合曲线为连续多张图像特征信息中部分特征信息之间的连线。如图15所示实施例，时间窗W5(以当前时刻为起点向前选择一段时间)，选取当前时刻在曲线上对应的点1502(当前点)，并在时间窗内的曲线上选取一个点1501(也可为多个点)，基于这些点拟合曲线，计算曲线的斜率，基于斜率判断时间窗W5内参考图像是否满足稳定条件。若满足稳定条件，停止拍摄参考图像，认为设备已经稳定，可获取目标物的目标图像。若不满足继续拍摄参考图像，时间窗沿着时间轴继续向右滑动，继续进行判断。其中，斜率越小，则表征拟合曲线越平稳，图像特征信息变化越小。
一个实施例中，计算连续多张图像特征信息的极差，根据获得的新的参考图像，可以不断得到新的极差，对各个极差进行拟合，得到拟合曲线。
如图16所示，基于时间窗W6内的特征信息得到第一个极差，不断拍摄得到新的参考图像，故将时间窗W6沿时间轴继续向右移动，分别得到第二个极差、第三个极差……，其中，时间窗W6中最后一个特征信息为当前最新获取参考图像的特征信息，基于图16所示虚线框内的各极差点拟合得到曲线L3，计算拟合曲线上最后一个点或最后连续多个点的斜率绝对值，若斜率绝对值小于相应阈值，则参考图像中存在满足稳定条件的图像，设备已经稳定。若不满足，继续拍摄参考图像，计算新的极差，并拟合曲线进行判断。
一个实施例中，取连续多张图像中特征信息的最大值与特征信息均值 之间差的绝对值，对各个差的绝对值进行拟合，得到拟合曲线。这里，均值为连续多张图像特征信息的均值或当前获得所有参考图像的特征信息的均值。
如图17所示，计算时间窗W7内特征信息最大值和均值之间差的绝对值，得到第一个差值，不断获取新的参考图像，故将时间窗W7继续沿时间轴向右移动，采用相同计算方法分别得到第二个差值、第三个差值……，这里，时间窗W7中最后一个特征信息为当前获取的最新参考图像的特征信息，基于虚线框各个差值的点得到拟合曲线L4，计算拟合曲线上最后一个点或最后连续多个点的斜率绝对值，若斜率绝对值小于相应阈值，则参考图像中存在满足稳定条件的图像，设备已经稳定。若不满足，继续拍摄参考图像，计算新的差值，并拟合曲线进行判断。
上述几个实施例为获得拟合曲线的示例性描述，本申请实施例中，对获得拟合曲线的方式不进行任何的限定。
上述S603：获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长；
如图18所示，包括以下步骤：
S6031B、获取所述待测样本从第一位置移动到第二位置或所述成像装置从第一位置移动到第二位置的移动速度和/或移动距离，将所述移动速度和/或移动距离作为第二位置的表征信息；
S6032B、根据所述第二位置的表征信息的变化，确定所述第一等待时长。
一个实施例中，图像分析设备中可设置有移动距离和/或移动速度与第一等待时长之间的对应关系，图像分析设备根据设置的关联关系确定当前移动距离和/或移动速度对应的第一等待时长。
其中，移动距离为移动轨迹的长度。若进行直线运动，则为两个位置 之间的直线距离。第一等待时长的大小与移动速度成正比例关系，即移动速度越大，第一等待时长越大，移动速度越小，第一等待时长越小。第一等待时长的大小与移动距离成正比例关系，即移动距离越大，第一等待时长越大，移动距离越小，第一等待时长越小。
在一个实施例中，若待测样本从第一位置移动到第二位置的距离越大，一般为了使待测样本能及时到达第二位置，移动速度也会越大，因此停止移动后带来的抖动也会较为剧烈，所需的第一等待时长就会越大。
图像分析设备还可包括：振动检测传感器；上述S603：获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长；
如图19所示，包括以下步骤：
S6031C、当所述待测样本从第一位置移动到第二位置或所述成像装置从第一位置移动到第二位置时，通过振动检测传感器获取所述第二位置待测样本或者成像装置的振动数据，将所述振动数据作为第二位置的表征信息；
S6032C、根据所述第二位置的表征信息的变化，确定所述第一等待时长。
振动传感器能够将机械量接收下来，并接收的机械量转换为与其成比例的电量，属于机电转换装置。其中，振动传感器的机电转换类型可包括：电动式、压电式、电涡流式、电感式、电容式、电阻式、光电式等。本发明实施例对振动传感器的机电转换类型不进行任何的限制。
振动传感器可包括：位移传感器、速度传感器、加速度传感器、力传感器、应变传感器、扭振传感器、扭矩传感器中的一个或多个的组合等。本发明实施例中对振动传感器的类型不进行任何的限定。
振动传感器对机械量进行机电转换后得到的电量数据为振动数据，当振动数据满足稳定条件，则表征图像分析设备已经稳定，此时可获取目标 图像，并确定第一等待时长。其中，第一等待时长为待测样本移动到第二位置或成像装置移动到第二位置的时刻至获取所述目标物的目标图像时刻之间间隔。
在一示例中，振动传感器为位移传感器，振动传感器检测的振动数据为图像分析设备的位移，稳定条件为：小于位移阈值，则当振动传感器检测的位移小于位移阈值时，确定振动数据满足稳定条件。
在一示例中，振动传感器为速度传感器，速度传感器检测的振动数据为图像分析设备的速度，稳定条件为：小于速度阈值，则当振动传感器检测的速度小于速度阈值时，确定振动数据满足稳定条件。
上述示例仅作为稳定条件的举例说明，在实际应用中，稳定条件可根据实际的需求进行设置，以判定图像分析设备是否稳定。
一个实施例中，所述图像分析设备成像方法，如图20所示，还包括：
S605、计算确定第一等待时长所需的工作时长，比较所述工作时长与预设时间阈值；
S606、如果所述工作时长大于或者等于所述预设时间阈值，停止确定第一等待时长；输出提示信息，和/或控制成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像。
这里，当确定第一等待时长所需的工作时长或等于预设时间阈值，则表征等待的时间过长，此时可输出提示信息进行报警，以提示用户当前的图像分析设备可能存在异常。
当确定第一等待时长所需的工作时长大于或等于预设时间阈值，可不再等待，通过成像装置直接对位于第二位置的待测样本中的目标物进行拍摄，作为待测样本中目标物的目标图像。
这里，S605确定的工作时长小于预设时长，则执行S604：待测样本在所述第二位置停留所述第一等待时长后，成像装置获取所述待测样本中目 标物的图像，作为所述目标物的目标图像。
上述S604：待测样本在所述第二位置停留所述第一等待时长后，成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像，包括：
选取所述参考图像中满足所述稳定条件的图像，作为所述目标物的目标图像。
这里，当通过拍摄参考图像确定第一等待时长的情况下，可将参考图像中满足稳定条件的图像直接作为目标图像，也可从中选取图像质量更好的图像作为目标图像。此时，不需要在第一等待时长后，再次进行图像的拍摄，从而节省时间，且减少图像分析设备的拍摄次数，提高设备效率。
上述S604：待测样本在所述第二位置停留所述第一等待时长后，成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像，包括：
待测样本在所述第二位置停留所述第一等待时长；
控制成像装置拍摄所述待测样本中目标物的图像，作为所述目标物的目标图像。
其中，图像分析设备在第一等待时长后，确定图像分析设备稳定的情况下，再次执行拍摄，拍摄位于所述第二位置的待测样本中目标物的图像，作为目标图像。这能够有效保证所获得目标图像的质量。
基于图2A、图2B、图3以及图4所示的图像分析设备，本发明实施例还提供一种图像分析设备成像方法，如图21所示，包括：
S2101：提供待测样本。
其中，待测样本可为血涂片，血涂片由待测血液样品制备得到。
S2102：驱动待测样本从第一位置移动到第二位置或所述成像装置从第一位置移动到所述第二位置。
其中，所述第二位置为所述待测样本中目标物位于所述成像装置拍摄范围内的位置。
其中，待测样本可为血涂片，目标物可为血涂片中任一种或多种细胞，如白细胞、红细胞和/或血小板。
如图7所示，成像装置对准的第一个拍摄位置为位置A，通过移动成像装置或待测样本涂片，使得成像装置对准的第二个拍摄位置为位置B。这里，位置A可称为第一位置，位置B可称为第二位置。其中，成像装置在第一位置和第二位置进行成像时，可使用同一个物镜。例如：在高倍镜下，对血涂片中不同位置的白细胞进行逐个拍摄的过程中，不更换高倍镜，采用同一高倍镜完成所述拍摄过程。
S2103：所述成像装置拍摄至少两张位于所述第二位置的所述待测样本中目标物的图像，作为目标物的参考图像；
成像装置可在待测样本或所述成像装置移动到第二位置时，立即开始拍摄所述参考图像；也可在待测样本或所述成像装置移动到第二位置，并经过第二等待时长后，开始拍摄所述参考图像。
所述第二等待时长为所述待测样本移动到所述第二位置的时刻或所述成像装置移动到所述第二位置的时刻至获取所述待测样本中目标物的参考图像的时刻之间的间隔。
图像分析设备可周期性地拍摄参考图像，可以边拍摄参考图像，边判断图像分析设备抖动情况，确定是否获取目标图像。其中，图像分析设备可基于帧率周期性地拍摄参考图像，此时，拍摄参考图像的周期T 拍＝1/帧率。
S2104：基于所述参考图像的特征信息，判断所述参考图像中是否存在 满足稳定条件的图像；
其中，所述特征信息包括：像素值、清晰度指标和位置信息中的一种或多种。
图像分析设备根据所述参考图像的特征信息的变化，判断图像分析设备何时会稳定，不再发生抖动，进而得到获取所述目标物的目标图像的时机。
当所述图像中未出现满足条件的图像时，执行S2103：所述成像装置继续执行拍摄位于所述第二位置的所述待测样本中目标物的图像，作为目标物的参考图像；当所述图像中出现满足稳定条件的图像时，执行S2105：获取位于所述第二位置的所述待测样本中目标物的图像，作为目标物的目标图像。
一个实施例中，当拍摄的所述参考图像中一张或连续多张图像满足所述稳定条件时，获取位于所述第二位置的所述待测样本中目标物的图像，作为目标物的目标图像。其中，所述连续多张图像为连续拍摄得到的多张图像，可至少为3张，也可为4张，5张，6张，8张等。
例如：获取参考图像包括：图像1、图像2、图像3……图像35，当图像35满足稳定条件，则表征图像分析设备已经稳定不再抖动，图像分析设备停止参考图像的拍摄，且获取目标物的目标图像。当图像35未满足稳定条件，则继续拍摄新的参考图像，并基于新的参考图像继续判断图像分析设备的抖动情况。
在一实施例中，上述S2104：基于所述参考图像的特征信息，判断所述参考图像中是否存在满足稳定条件的图像，如图22所示，包括：
S2104A：基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像。
例如：获取参考图像包括：连续拍摄得到的图像1、图像2、图像3…… 图像35，若当前连续拍摄获得的几张最新参考图像如：图像33、图像34、图像35均满足稳定条件时，表征图像分析设备已经稳定不再抖动，图像分析设备停止参考图像的拍摄，且获取目标物的目标图像。当未满足上述稳定条件，则继续拍摄新的参考图像，并基于新的参考图像判断图像分析设备的抖动情况。
在一实施例中，上述S2104A：所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，如图23所示，包括：
SA11：基于至少两个所述参考图像的特征信息的差异；
SA12：如所述差异符合第一阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
一个实施例中，连续比较相邻的所述参考图像的特征信息的差异。
其中，若连续多张参考图像对应的特征信息差异均符合第一阈值范围，则表征有连续多张参考图像满足稳定条件，更能表明设备目前已经稳定，可以清晰的获取所述目标物的目标图像。
一个实施例中，比较相邻两个所述参考图像的特征信息，获得所述参考图像对应的特征信息差，如像素差、位置信息差等；将所述参考图像对应的特征信息差与第一阈值进行比较；若存在所述特征信息差小于第一阈值的情况，则表征所述参考图像中存在满足所述稳定条件的图像。其中，所述特征信息差可取绝对值。
另一实施例中，若连续多张所述参考图像对应的特征信息差均小于第一阈值，则认为分析设备已经稳定，可获取目标物的目标图像。其中，所述特征信息差可取绝对值。
比如：获取的参考图像包括：图像1、图像2、图像3、图像4、图像5……，图像1和图像2的特征信息之间的差(其中，所述特征信息差可取绝对值)， 得到图像2对应的特征信息差；计算图像2和图像3的特征信息之间的差，得到图像3对应的特征信息差……，以此类推计算，即不断计算当前获取的最新图像与上一张图像的差。当图像10对应的特征信息差的小于第一阈值，或图像8、图像9和图像10对应的特征信息差均小于第一阈值，则认为设备不再抖动，已经稳定，故停止参考图像的获取，并停止特征信息差的计算，获取目标物的目标图像。
在一示例中，将参考图像中的一图像作为对比图像，将对比图像之后的参考图像分别和对比图像的特征信息进行比较，得到各参考图像对应的特征信息差(其中，所述特征信息差可取绝对值)。对比图像可为参考图像中任一图像。比如：参考图像集合中的参考图像包括：图像1、图像2、图像3、图像4、图像5……，对比图像为图像1，计算图像1和图像2的特征信息之间的差，即差1；计算图像1和图像3的特征信息之间的差，即差2，将差1和差2比较，得到图像3对应的特征信息差；计算图像1和图像4的特征信息之间的差，即差3，将差2和差3进行比较，得到图像3对应的特征信息差……，以此类推。当图像10对应的特征信息差的小于第一阈值，或图像8、图像9和图像10对应的特征信息差均小于第一阈值，则停止参考图像的拍摄，并停止特征信息差的计算，获取目标物的目标图像。
在一实施例中，上述S2104A：所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，如图24所示，包括：
SA21：计算连续多张所述参考图像的特征信息和/或特征信息差的离散程度；
SA22：将所述离散程度与第二阈值范围进行比较；
SA23：若所述离散程度符合第二阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
其中，离散程度是指各个特征信息或特征信息差之间的差异程度。离散程度可包括极差、平均差和标准差等。本实施例中对离散程度的表征方式不进行任何的限定。其中，特征信息可为像素值、清晰度指标和位置信息中的一种或多种。
此外，计算离散程度时，还可直接计算当前获取的连续多张最新图像(即以获取的最新图像为起点向前连续选取几张图像)进行计算。
以计算连续三个像素差的离散程度为例，当最新拍摄的参考图像为图像5，则计算图像3、图像4、图像5对应的像素差的离散程度3，当计算的离散程度3大于离散程度阈值，则继续获取新的参考图像：图像6，并计算图像4、图像5、图像6对应的像素差的离散程度4，当计算的离散程度4大于离散程度阈值，则继续获取新的参考图像,以此类推。当图像10、图像11、图像12对应的像素差的离散程度10小于离散程度阈值，则图像10、图像11、图像12为满足稳定条件的图像，认为设备已经稳定不再抖动，停止参考图像的获取。
其他实施例中，除清晰度指标、像素差外，还可计算位置信息及其差、清晰度指标的差、像素值等的离散程度，方法类似上述实施例，此处不再一一举例。
在一实施例中，上述S2104A：所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，如图25所示，包括：
SA31：基于所述参考图像的特征信息获得拟合曲线，计算所述拟合曲线斜率的绝对值；
SA32：将所述拟合曲线斜率的绝对值与第三阈值范围进行比较；
SA33：若所述拟合曲线斜率的绝对值符合所述第三阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
此时，可认为分析设备已经稳定。
优选的，还计算所述拟合曲线斜率变化的绝对值，如果所述拟合曲线斜率的绝对值和所述拟合曲线斜率变化的绝对值均符合阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。能够更精确地判断出图像分析设备是否稳定。
其中，拟合曲线的斜率可为拟合曲线的一阶导，拟合曲线的斜率变化可为拟合曲线的二阶导。
一个实施例中，拟合曲线可基于当前获取参考图像所有特征信息的包络线，也可基于部分特征信息的包络线。
一个实施例中，以最新拍摄的参考图像的特征信息为起点，选取连续多个参考图像的特征信息做拟合，得到拟合曲线。例如：选取数量为3，当最新获取的图像为图像3，则将图像1、图像2和图像3的特征信息做拟合，得到拟合曲线1，计算拟合曲线上最后一个点或连续多个点的斜率，来判断最新获取的图像是否满足稳定条件。若不满足，继续获取新的参考图像像4，再将图像2、图像3和图像4的特征信息做拟合，得到拟合曲线2，再计算拟合曲线上最后一个点或连续多个点的斜率，来判断最新获取的图像是否满足稳定条件，若斜率小于相应阈值，则认为图像2、图像3和图像4为满足稳定条件的图像，表明分析设备已经稳定，不再获取新的参考图像。
一个实施例中，拟合曲线为连续多张图像特征信息中部分特征信息之间的连线。
一个实施例中，计算连续多张图像特征信息的极差，根据获得的新的参考图像，可以不断得到新的极差，对各个极差进行拟合，得到拟合曲线。
一个实施例中，取连续多张图像中特征信息的最大值与特征信息均值之间差的绝对值，对各个差的绝对值进行拟合，得到拟合曲线。这里，均值为连续多张图像特征信息的均值或当前获得所有参考图像的特征信息的 均值。
上述几个实施例为获得拟合曲线的示例性描述，本申请实施例中，对获得拟合曲线的方式不进行任何的限定。
这里，关于图21所示的图像分析设备成像方法的具体描述，可参见前文图6所示的图像分析设备成像方法中：基于参考图像判断图像分析设备是否稳定相关的具体描述，这里不再赘述。
本发明实施例提供的图像分析设备成像方法，在待测样本移动到第二位置或成像装置移动到第二位置后，执行拍摄，且将拍摄的位于第二位置的待测样本中目标物的图像作为参考图像，当参考图像中包括满足稳定条件的图像，则确定图像分析设备稳定，当参考图像中包括不满足稳定条件的图像，则继续获取参考图像，以基于获取的参考图像确定图像分析设备是否稳定，利用在第二位置拍摄的参考图像能够准确的判断图像分析设备是否稳定，使得待测样本移动到第二位置或成像装置移动到第二位置的时间至获取待分析的目标图像的时间之间的时间间隔根据第二位置动态变化，且与移动的位置相适应，在保证拍摄的细胞图像清晰的情况下，提高时间资源的利用率，提高图像分析设备的工作效率。
下面，以待测样本为血涂片为例，通过具体的应用场景对本发明实施例提供的图像分析设备成像方法进行举例说明。
图像分析设备通过移动装置或血涂片将血涂片相对于成像装置的位置从A位置(X1，Y1)移动到B位置(X2，Y2)，并在血涂片相对于成像装置的位置移动到B位置之后，每间隔一段预设时间拍摄一幅细胞图像，作为参考图像。
图像分析设备对拍摄的参考图像进行分析，如果通过参考图像判断图像分析设备已经稳定，则开始进行自动对焦并执行拍摄工作，对血涂片的位于拍摄区域的细胞进行拍摄，得到细胞图像，并记录等待图像分析设备 稳定所耗费时间为第一等待时长ΔT；否则，继续拍摄参考图像，基于新拍摄的参考图像来判断图像分析设备是否已经稳定。
这里，图像分析设备可基于连续多个参考图像来判断图像分析设备是否稳定。在一示例中，图像分析设备拍摄到的参考图像包括：图像1、图像2、图像3，则基于图像1、图像2、图像3来判断图像分析设备是否稳定，当确定图像分析设备未稳定，则继续拍摄新的参考图像：图像4，并基于图像2、图像3和图像4来判断图像分析设备是否稳定，以此类推，当确定图像分析设备稳定的情况下，不再继续拍摄新的参考图像，否则继续拍摄新的参考图像，并继续以新的参考图像来判断图像分析设备是否稳定。
这里，当图像分析设备判断自身稳定时，对应的参考图像可称为满足稳定条件的图像。
其中，图像分析设备对参考图像进行分析的方法包括：
比较当前参考图像与之前一系列参考图像的差异，如果差异较小则表示图像分析设备稳定。这里，对于当前参考图像与之前一系列参考图像，可分别比较中相邻的两幅参考图像之间的差异。
比较相邻的两幅图像之间的差异的方式可包括以下三种方式：
两幅图像的像素值做差、对两幅图像配准之后判断两幅图像的X/Y的平移量、或计算两幅图像的对焦度的变化量。
对于当前参考图像与之前一系列参考图像，当计算的上述差异中的一种差异或多种差异小于对应的阈值即可认为图像分析设备稳定。
其中，如果ΔT超过预设的上限值ΔT_max，则报警提示，或者不再等待，直接开始拍摄待分析的目标图像。
在一实施例中，图像分析设备拍摄参考图像的间隔时间可为相机的最小帧所需时间。
在一实施例中，图像分析设备确定连续N幅参考图像的差异小于预设 值时，确定图像分析设备稳定。其中，N大于等于3。
本发明实施例还提供一种图像分析装置，实施于如图2A、图2B、图3和4所示的图像处理设备，如图2A所示，包括：成像装置201、移动装置202和控制器203；
成像装置201包括相机2011和透镜组2012，配置为拍摄待测样本中目标物的图像；
移动装置202，具有放置所述待测样本的平台2021和驱动部2022，透镜组2022位于相机2011和平台2021之间，驱动部2022使平台2021和成像装置201进行相对运动，以便成像装置201拍摄所述待测样本的特定区域的目标物图像；
控制器203，与成像装置201和移动装置202耦联，并配置为：
控制待测样本与成像装置从第一位置相对移动到第二位置，其中，在所述第二位置，所述待测样本中目标物位于所述成像装置的拍摄范围内；获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长；所述待测样本在第二位置停留所述第一等待时长后，获取所述待测样本中的目标物图像，作为所述目标物的目标图像。
在一实施例中，所述获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长，包括：
所述成像装置在所述第二位置拍摄至少两张所述待测样本中目标物的参考图像，所述参考图像的特征信息作为第二位置的表征信息；
根据所述第二位置的表征信息的变化，确定所述第一等待时长。
在一实施例中，所述根据所述参考图像的特征信息的变化，确定所述第一等待时长，包括：
基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像；
如果存在满足所述稳定条件的图像，则确定所述第一等待时长；
如果不存在满足所述稳定条件的图像，则继续拍摄参考图像并判断是否存在满足稳定条件的图像；
优选的，当拍摄的所述参考图像中连续多张图像满足所述稳定条件时，确定所述第一等待时长。
在一实施例中，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
比较至少两个所述参考图像的特征信息的差异；
如所述差异符合第一阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；
优选的，连续比较相邻的所述参考图像的特征信息的差异。
在一实施例中，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
计算连续多张所述参考图像的特征信息和/或特征信息差的离散程度；
将所述离散程度与第二阈值范围进行比较；
若所述离散程度符合第二阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
在一实施例中，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
基于所述参考图像的特征信息获得曲线，判断曲线的变化趋势是否平坦；
一个实施例中，基于所述参考图像的特征信息获得曲线，判断曲线的变化趋势是否平坦，包括以下步骤：
基于所述参考图像的特征信息获得拟合曲线，计算所述拟合曲线斜率的绝对值；将所述拟合曲线斜率的绝对值与第三阈值范围进行比较；若所 述拟合曲线斜率的绝对值符合所述第三阈值范围，则表征所述曲线的变化趋势平坦，即所述参考图像中存在满足所述稳定条件的图像；
优选的，还计算所述拟合曲线斜率变化的绝对值，如果所述拟合曲线斜率的绝对值和所述拟合曲线斜率变化的绝对值均符合阈值范围，则表征所述曲线的变化趋势平坦，即所述参考图像中存在满足所述稳定条件的图像。
在一实施例中，所述参考图像的特征信息包括：像素值、清晰度指标和位置信息中的一种或多种。
在一实施例中，控制器203，还配置为：
当特征信息为位置信息时，将相邻的所述参考图像进行配准，计算得到所述相邻参考图像之间位置信息的差值，如所述差值符合阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；
优选的，查找相邻的所述参考图像之间相关的区域；在相邻的所述参考图像基于所述相关的区域重叠的情况下，确定所述相邻参考图像中指定位置之间的位置差。
在一实施例中，所述获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长，包括：
获取所述待测样本或成像装置从第一位置移动到第二位置的移动速度和/或移动距离，将所述移动速度和/或移动距离作为第二位置的表征信息；
根据所述第二位置的表征信息的变化，确定所述第一等待时长。
在一实施例中，所述图像分析设备还包括：振动检测传感器；所述获取第二位置的表征信息，根据第二位置的表征信息决定第一等待时长，包括：
当所述待测样本从第一位置移动到第二位置或所述成像装置从第一位置移动到第二位置时，通过振动检测传感器获取所述第二位置待测样本或 者成像装置的振动数据，将所述振动数据作为第二位置的表征信息；
根据所述第二位置的表征信息的变化，确定所述第一等待时长。
在一实施例中，控制器203，还配置为：
计算确定第一等待时长所需的工作时长，比较所述工作时长与预设时间阈值；
如果所述工作时长大于或者等于所述预设时间阈值，停止确定所述第一等待时长；
输出提示信息，和/或控制所述成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像。
在一实施例中，所述待测样本在所述第二位置停留所述第一等待时长后，成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像包括：
选取所述参考图像中满足所述稳定条件的图像，作为所述目标物的目标图像。
在一实施例中，所述待测样本在所述第二位置停留所述第一等待时长后，成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像包括：
待测样本在所述第二位置停留所述第一等待时长；
控制所述成像装置拍摄所述待测样本中目标物的图像，作为所述目标物的目标图像。
在一实施例中，所述第一等待时长为所述待测样本移动到所述第二位置的时刻或所述成像装置移动到所述第二位置的时刻至获取所述目标物的目标图像的时刻之间的间隔。
在一实施例中，控制器203，还配置为：
将所述待测样本移动到第二位置或所述成像装置移动到第二位置，并 经过第二等待时长后，所述成像装置拍摄位于所述第二位置的所述待测样本中目标物的图像，作为参考图像。
在一实施例中，所述待测样本为血涂片，和/或所述图像分析设备为自动化阅片机。
本发明实施例还提供一种图像分析装置，实施于如图2A、图2B、图3和4所示的图像处理设备，如图2A所示，包括：
成像装置201、移动装置202和控制器203；
成像装置201包括相机2011和透镜组2012，配置为拍摄待测样本中目标物的图像；
移动装置202，具有放置所述待测样本的平台2021和驱动部2022，2012透镜组位于相机2011和平台2021之间，驱动部2022使平台2021和成像装置201进行相对运动，以便成像装置201拍摄所述待测样本的特定区域的目标物图像；
控制器203，与成像装置201和移动装置202耦联，并配置为：
控制所述待测样本与成像装置从第一位置相对移动到第二位置，在所述第二位置，待测样本中的目标物位于所述成像装置的拍摄范围内，并控制所述成像装置拍摄至少两张所述第二位置的所述待测样本中的目标物的图像，作为目标物的参考图像；基于所述参考图像中的特征信息，判断所述参考图像中是否存在满足稳定条件的图像；当所述图像中出现满足稳定条件的图像时，获取位于所述第二位置的所述待测样本中目标物的图像，作为目标物的目标图像；当所述图像中未出现满足条件的图像时，控制所述成像装置在所述第二位置继续拍摄参考图像。
在一实施例中，基于所述参考图像的特征信息，判断所述参考图像中是否存在满足稳定条件的图像，包括：
基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否 存在满足稳定条件的图像。
在一实施例中，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
比较至少两个所述参考图像的特征信息的差异；
如所述差异符合第一阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；
优选的，连续比较相邻的所述参考图像的特征信息的差异。
在一实施例中，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
计算连续多张所述参考图像的特征信息和/或特征信息差的离散程度；
将所述离散程度与第二阈值范围进行比较；
若所述离散程度符合第二阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
在一实施例中，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
基于所述参考图像的特征信息获得拟合曲线，计算所述拟合曲线斜率的绝对值；将所述拟合曲线斜率的绝对值与第三阈值范围进行比较；若所述拟合曲线斜率的绝对值符合所述第三阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；
优选的，还计算所述拟合曲线斜率变化的绝对值，如果所述拟合曲线斜率的绝对值和所述拟合曲线斜率变化的绝对值均符合阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
在一实施例中，所述参考图像的特征信息包括：像素值、清晰度指标和位置信息中的一种或多种。
在一实施例中，所述获取位于所述第二位置的所述待测样本中目标物 的图像，作为目标物的目标图像，包括：
选取所述参考图像中满足所述稳定条件的图像，作为所述目标物的目标图像。
在一实施例中，当所述图像中出现满足稳定条件的图像时，获取位于所述第二位置的所述待测样本中目标物的图像，作为目标物的目标图像，包括：
当所述图像中出现满足稳定条件的图像时，控制所述成像装置拍摄所述待测样本中目标物的图像，作为所述目标物的目标图像。
在一实施例中，控制器203，还配置为：
将所述待测样本移动到第二位置或所述成像装置移动到第二位置，并经过第二等待时长后，所述成像装置拍摄位于所述第二位置的所述待测样本中目标物的图像，作为参考图像。
在一实施例中，所述待测样本为血涂片，和/或所述图像分析设备为自动化阅片机。
本发明实施例提供的图像分析装置中的控制器，可配置为执行上述图6或图21所示的图像分析设备成像方法的步骤。
本发明实施例再提供一种存储介质，即计算机可读存储介质，所述存储介质上存储有可执行程序，所述可执行程序被控制器执行时，实现上述执行的图像分析设备成像方法的步骤。
在一示例中，控制器可以为CPU、GPU或其它具有运算能力的芯片。
存储器中装有操作系统和应用程序等供控制器执行的各种计算机程序及执行该计算机程序所需的数据。另外，在样本检测过程中，如有需要本地存储的数据，均可以存储到存储器中。
以上介质实施例的描述，与上述方法实施例的描述是类似的，具有同方法实施例相似的有益效果。对于本发明存储介质实施例中未披露的技术 细节，请参照本发明方法实施例的描述而理解。
本发明实施例中，如果以软件功能模块的形式实现上述的图像分析设备成像方法，并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明实施例的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机、服务器、或者网络设备等)执行本发明各个实施例所述方法的全部或部分。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read Only Memory)、磁碟或者光盘等各种可以存储程序代码的介质。这样，本发明实施例不限制于任何特定的硬件和软件结合。
应理解，说明书通篇中提到的“一个实施例”或“一实施例”意味着与实施例有关的特定特征、结构或特性包括在本发明的至少一个实施例中。因此，在整个说明书各处出现的“在一个实施例中”或“在可选地实施例中”未必一定指相同的实施例。此外，这些特定的特征、结构或特性可以任意适合的方式结合在一个或多个实施例中。应理解，在本发明的各种实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本发明实施例的实施过程构成任何限定。上述本发明实施例序号仅仅为了描述，不代表实施例的优劣。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者装置不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者装置所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者装置中还存在另外的相同要素。
在本发明所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，如：多个单元或组件可以结合，或可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的各组成部分相互之间的耦合、或直接耦合、或通信连接可以是通过一些接口，设备或单元的间接耦合或通信连接，可以是电性的、机械的或其它形式的。
上述作为分离部件说明的单元可以是、或也可以不是物理上分开的，作为单元显示的部件可以是、或也可以不是物理单元；既可以位于一个地方，也可以分布到多个网络单元上；可以根据实际的需要选择其中的部分或全部单元来实现本实施例方案的目的。
另外，在本发明各实施例中的各功能单元可以全部集成在一个处理单元中，也可以是各单元分别单独作为一个单元，也可以两个或两个以上单元集成在一个单元中；上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：移动存储设备、只读存储器(Read Only Memory，ROM)、磁碟或者光盘等各种可以存储程序代码的介质。
或者，本发明上述集成的单元如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明实施例的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算 机、服务器、或者网络设备等)执行本发明各个实施例所述方法的全部或部分。而前述的存储介质包括：移动存储设备、ROM、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以所述权利要求的保护范围为准。

Claims (32)

  1. 一种图像分析设备成像方法，所述图像分析设备包括成像装置，所述方法包括：
    提供待测样本；
    驱动待测样本从第一位置移动到第二位置，或成像装置第一位置移动到所述第二位置，其中所述第二位置为所述待测样本中目标物位于所述成像装置拍摄范围内的位置；
    获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长；
    待测样本在所述第二位置停留所述第一等待时长后，成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像。
  2. 根据权利要求1所述的方法，所述获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长，包括：
    所述待测样本或所述成像装置移动到所述第二位置，所述成像装置拍摄至少两张所述待测样本中目标物的参考图像，所述参考图像的特征信息作为第二位置的表征信息；
    根据所述第二位置的表征信息的变化，确定所述第一等待时长。
  3. 根据权利要求2所述的方法，所述根据所述参考图像的特征信息的变化，确定所述第一等待时长，包括：
    基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像；
    如果存在满足所述稳定条件的图像，则确定所述第一等待时长；
    如果不存在满足所述稳定条件的图像，则继续拍摄参考图像并判断是否存在满足稳定条件的图像；
    优选的，当拍摄的所述参考图像中连续多张图像满足所述稳定条件时， 确定所述第一等待时长。
  4. 根据权利要求3所述的方法，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
    比较至少两个所述参考图像的特征信息的差异；
    如所述差异符合第一阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；
    优选的，连续比较相邻的所述参考图像的特征信息的差异。
  5. 根据权利要求3所述的方法，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
    计算连续多张所述参考图像的特征信息和/或特征信息差的离散程度；
    将所述离散程度与第二阈值范围进行比较；
    若所述离散程度符合第二阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
  6. 根据权利要求3所述的方法，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
    基于所述参考图像的特征信息获得拟合曲线，计算所述拟合曲线斜率的绝对值；将所述拟合曲线斜率的绝对值与第三阈值范围进行比较；若所述拟合曲线斜率的绝对值符合所述第三阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；
    优选的，还计算所述拟合曲线斜率变化的绝对值，如果所述拟合曲线斜率的绝对值和所述拟合曲线斜率变化的绝对值均符合阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
  7. 根据权利要求2-6任一项所述的方法，所述参考图像的特征信息包括：像素值、清晰度指标和位置信息中的一种或多种。
  8. 根据权利要求7所述的方法，当特征信息为位置信息时，所述方法 包括：
    将相邻的所述参考图像进行配准，计算得到所述相邻参考图像之间位置信息的差值，如所述差值符合阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；
    优选的，查找相邻的所述参考图像之间相关的区域；在相邻的所述参考图像基于所述相关的区域重叠的情况下，确定所述相邻参考图像中指定位置之间的位置差。
  9. 根据权利要求1所述的方法，所述获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长，包括：
    获取所述待测样本从第一位置移动到第二位置或所述成像装置从第一位置移动到第二位置的移动速度和/或移动距离，将所述移动速度和/或移动距离作为第二位置的表征信息；
    根据所述第二位置的表征信息的变化，确定所述第一等待时长。
  10. 根据权利要求1所述的方法，所述图像分析设备还包括：振动检测传感器；所述获取第二位置的表征信息，根据第二位置的表征信息决定第一等待时长，包括：
    当所述待测样本从第一位置移动到第二位置或所述成像装置从第一位置移动到第二位置时，通过振动检测传感器获取所述第二位置待测样本或者成像装置的振动数据，将所述振动数据作为第二位置的表征信息；
    根据所述第二位置的表征信息的变化，确定所述第一等待时长。
  11. 根据权利要求1至10任一项所述的方法，所述方法还包括：
    计算确定第一等待时长所需的工作时长，比较所述工作时长与预设时间阈值；
    如果所述工作时长大于或者等于所述预设时间阈值，停止确定第一等待时长；输出提示信息，和/或控制成像装置获取所述待测样本中目标物的 图像，作为所述目标物的目标图像。
  12. 根据权利要求2至8任一项所述的方法，所述待测样本在所述第二位置停留所述第一等待时长后，成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像包括：
    选取所述参考图像中满足所述稳定条件的图像，作为所述目标物的目标图像。
  13. 根据权利要求1至11任一项所述的方法，所述待测样本在所述第二位置停留所述第一等待时长后，成像装置获取所述待测样本中目标物的图像，作为所述目标物的目标图像包括：
    待测样本在所述第二位置停留所述第一等待时长；
    控制成像装置拍摄所述待测样本中目标物的图像，作为所述目标物的目标图像。
  14. 根据权利要求1至13任一项所述的方法，所述第一等待时长为所述待测样本移动到所述第二位置的时刻或所述成像装置移动到所述第二位置的时刻至获取所述目标物的目标图像的时刻之间的间隔。
  15. 根据权利要求1至14任一项所述的方法，所述方法还包括：
    将所述待测样本移动到第二位置或所述成像装置移动到第二位置，并经过第二等待时长后，通过所述成像装置拍摄位于所述第二位置的所述待测样本中目标物的图像，作为参考图像。
  16. 根据权利要求1至15任一项所述的方法，所述待测样本为血涂片，和/或所述图像分析设备为自动化阅片机。
  17. 一种图像分析设备的成像方法，所述分析设备包括成像装置，所述方法包括：
    提供待测样本；
    驱动待测样本从第一位置移动到第二位置或所述成像装置从第一位置 移动到所述第二位置，其中所述第二位置为所述待测样本中目标物位于所述成像装置拍摄范围内的位置；
    所述成像装置拍摄至少两张位于所述第二位置的所述待测样本中目标物的图像，作为目标物的参考图像；
    基于所述参考图像的特征信息，判断所述参考图像中是否存在满足稳定条件的图像；
    当所述图像中未出现满足条件的图像时，所述成像装置继续拍摄位于所述第二位置的所述待测样本中目标物的图像，作为目标物的参考图像；
    当所述图像中出现满足稳定条件的图像时，获取位于所述第二位置的所述待测样本中目标物的图像，作为目标物的目标图像。
  18. 根据权利要求17所述的方法，基于所述参考图像的特征信息，判断所述参考图像中是否存在满足稳定条件的图像，包括：
    基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像。
  19. 根据权利要求18所述的方法，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
    比较至少两个所述参考图像的特征信息的差异；
    如所述差异符合第一阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；
    优选的，连续比较相邻的所述参考图像的特征信息的差异。
  20. 根据权利要求18所述的方法，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
    计算连续多张所述参考图像的特征信息和/或特征信息差的离散程度；
    将所述离散程度与第二阈值范围进行比较；
    若所述离散程度符合第二阈值范围，则表征所述参考图像中存在满足 所述稳定条件的图像。
  21. 根据权利要求18所述的方法，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
    基于所述参考图像的特征信息获得拟合曲线，计算所述拟合曲线斜率的绝对值；将所述拟合曲线斜率的绝对值与第三阈值范围进行比较；若所述拟合曲线斜率的绝对值符合所述第三阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；
    优选的，还计算所述拟合曲线斜率变化的绝对值，如果所述拟合曲线斜率的绝对值和所述拟合曲线斜率变化的绝对值均符合阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
  22. 根据权利要求17至21任一项所述的方法，所述参考图像的特征信息包括：像素值、清晰度指标和位置信息中的一种或多种。
  23. 一种图像分析装置，包括：
    成像装置、移动装置和控制器；
    所述成像装置包括相机和透镜组，配置为拍摄待测样本中目标物的图像；
    所述移动装置，具有放置所述待测样本的平台和驱动部，所述透镜组位于所述相机和所述平台之间，所述驱动部使所述平台和成像装置进行相对运动，以便成像装置拍摄所述待测样本的特定区域的目标物图像；
    所述控制器，与所述成像装置和移动装置耦联，并配置为：
    控制待测样本与成像装置从第一位置相对移动到第二位置，其中在所述第二位置，所述待测样本中目标物位于所述成像装置的拍摄范围内；获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长；所述待测样本在第二位置停留所述第一等待时长后，获取所述待测样本中的目标物图像，作为所述目标物的目标图像。
  24. 根据权利要求23所述的图像分析装置，所述获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长，包括：
    所述成像装置在所述第二位置拍摄至少两张所述待测样本中目标物的参考图像，所述参考图像的特征信息作为第二位置的表征信息；
    根据所述第二位置的表征信息的变化，确定所述第一等待时长。
  25. 根据权利要求23所述的图像分析装置，所述获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长，包括：
    获取所述待测样本或成像装置从第一位置移动到第二位置的移动速度和/或移动距离，将所述移动速度和/或移动距离作为第二位置的表征信息；
    根据所述第二位置的表征信息的变化，确定所述第一等待时长。
  26. 根据权利要求23所述的图像分析装置，所述分析装置还包括：振动检测传感器；所述获取第二位置的表征信息，所述第二位置的表征信息决定第一等待时长，包括：
    当所述待测样本从第一位置移动到第二位置或所述成像装置从第一位置移动到第二位置时，通过振动检测传感器获取所述第二位置待测样本或者成像装置的振动数据，将所述振动数据作为第二位置的表征信息；
    根据所述第二位置的表征信息的变化，确定所述第一等待时长。
  27. 一种图像分析装置，包括：
    成像装置、移动装置和控制器；
    所述成像装置包括相机和透镜组，配置为拍摄待测样本中目标物的图像；
    所述移动装置，具有放置所述待测样本的平台和驱动部，所述透镜组位于所述相机和所述平台之间，所述驱动部使所述平台和成像装置进行相对运动，以便成像装置拍摄所述待测样本的特定区域的目标物图像；
    所述控制器，与所述成像装置和移动装置耦联，并配置为：
    控制所述待测样本与成像装置从第一位置相对移动到第二位置，在所 述第二位置，待测样本中的目标物位于所述成像装置的拍摄范围内，并控制所述成像装置拍摄至少两张所述第二位置的所述待测样本中的目标物的图像，作为目标物的参考图像；基于所述参考图像中的特征信息，判断所述参考图像中是否存在满足稳定条件的图像；当所述图像中出现满足稳定条件的图像时，获取位于所述第二位置的所述待测样本中目标物的图像，作为目标物的目标图像；当所述图像中未出现满足条件的图像时，控制所述成像装置在所述第二位置继续拍摄参考图像。
  28. 根据权利要求27所述的图像分析装置，所述基于参考图像中的特征信息，判断所述参考图像中是否存在满足稳定条件的图像，包括：
    基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像。
  29. 根据权利要求28所述的图像分析装置，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
    比较至少两个所述参考图像的特征信息的差异；
    如所述差异符合第一阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；
    优选的，连续比较相邻的所述参考图像的特征信息的差异。
  30. 根据权利要求28所述的图像分析装置，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
    计算连续多张所述参考图像的特征信息和/或特征信息差的离散程度；
    将所述离散程度与第二阈值范围进行比较；
    若所述离散程度符合第二阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
  31. 根据权利要求28所述的图像分析装置，所述基于至少两个参考图像的特征信息，判断获得的所述参考图像中是否存在满足稳定条件的图像，包括：
    基于所述参考图像的特征信息获得拟合曲线，计算所述拟合曲线斜率的绝对值；将所述拟合曲线斜率的绝对值与第三阈值范围进行比较；若所述拟合曲线斜率的绝对值符合所述第三阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像；
    优选的，还计算所述拟合曲线斜率变化的绝对值，如果所述拟合曲线斜率的绝对值和所述拟合曲线斜率变化的绝对值均符合阈值范围，则表征所述参考图像中存在满足所述稳定条件的图像。
  32. 根据权利要求27至31任一项所述的图像分析装置，所述参考图像的特征信息包括：像素值、清晰度指标和位置信息中的一种或多种。
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