CN113040812B - Medical image analysis method, medical image analysis device, computer equipment and storage medium - Google Patents
Medical image analysis method, medical image analysis device, computer equipment and storage medium Download PDFInfo
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/48—Diagnostic techniques
- A61B8/481—Diagnostic techniques involving the use of contrast agent, e.g. microbubbles introduced into the bloodstream
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
- A61B5/0062—Arrangements for scanning
- A61B5/0066—Optical coherence imaging
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
- A61B8/0891—Detecting organic movements or changes, e.g. tumours, cysts, swellings for diagnosis of blood vessels
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
- A61B8/5238—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for combining image data of patient, e.g. merging several images from different acquisition modes into one image
- A61B8/5261—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for combining image data of patient, e.g. merging several images from different acquisition modes into one image combining images from different diagnostic modalities, e.g. ultrasound and X-ray
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Abstract
The application relates to a medical image analysis method, a medical image analysis device, computer equipment and a storage medium. The method comprises the following steps: acquiring an angiographic image to be analyzed; obtaining a first region of interest in the angiographic image from the angiographic image; analyzing the first region of interest to obtain first parameter information corresponding to the first region of interest; obtaining an analysis result according to the first parameter information; the analysis result is used for indicating whether the first region of interest meets a preset first condition. By adopting the method, the analysis result for indicating whether the first region of interest in the angiographic image to be analyzed meets the preset first condition can be accurately obtained, and the accuracy of the analysis result of the angiographic image to be analyzed is improved.
Description
Technical Field
The present application relates to the field of medical image technology, and in particular, to a medical image analysis method, apparatus, computer device, and storage medium.
Background
The bioabsorbable stent has the advantages of avoiding coronary artery metallization caused by long-term existence of the metal stent and the like, and is widely applied to interventional therapy of coronary heart disease. However, before the bioabsorbable stent is implanted in a human body, it is first necessary to determine whether the bioabsorbable stent can be implanted by combining the lesion site of the patient and the instructions for using the bioabsorbable stent.
In the traditional technology, a doctor marks blood vessels in an angiography image of a patient manually, a coronary angiography quantitative analysis method is used for acquiring blood vessel parameters of the patient, and whether the patient is suitable for implanting a bioabsorbable stent is judged according to the acquired blood vessel parameters.
However, the conventional judging method has a problem that the judging efficiency is low.
Disclosure of Invention
In view of the foregoing, there is a need for a medical image analysis method, apparatus, computer device, and storage medium that can improve the efficiency of determining whether a patient is suitable for implantation of a bioabsorbable stent.
A medical image analysis method, the method comprising:
acquiring an angiographic image to be analyzed;
obtaining a first region of interest in the angiographic image according to the angiographic image;
analyzing the first region of interest to obtain first parameter information corresponding to the first region of interest;
obtaining an analysis result according to the first parameter information; the analysis result is used for indicating whether the first region of interest meets a preset first condition.
In one embodiment, the obtaining the first region of interest in the angiographic image according to the angiographic image includes:
Inputting the angiography image into a preset positioning network, and obtaining a first region of interest in the angiography image through the positioning network.
In one embodiment, the first parameter information includes: the method comprises the steps of determining position information of a first region of interest, vascular distribution information in a preset range in the first region of interest, vascular morphology information in the preset range and plaque quantitative analysis information of the first region of interest.
In one embodiment, the method further comprises:
acquiring an intracavity image corresponding to the angiographic image;
determining a second region of interest corresponding to the first region of interest in the intra-cavity image;
analyzing the second region of interest to obtain second parameter information corresponding to the second region of interest;
and obtaining the analysis result according to the first parameter information and the second parameter information.
In one embodiment, the determining, in the intra-cavity image, a second region of interest corresponding to the first region of interest includes:
calculating a first blood vessel diameter distribution map corresponding to the angiographic image and a second blood vessel diameter distribution map corresponding to the intracavity image;
Calculating a first vessel topological structure key point corresponding to the angiography image and a second vessel topological structure key point corresponding to the intracavity image;
and determining a second region of interest corresponding to the first region of interest according to the first vessel diameter distribution diagram, the second vessel diameter distribution diagram, the first vessel topological structure key point and the second vessel topological structure key point.
In one embodiment, the second parameter information includes: the position information of the second region of interest, the vascular distribution information within a preset range and the vascular morphology information within the preset range in the second region of interest, and the plaque quantification analysis information of the second region of interest.
In one embodiment, the intra-luminal image comprises an intravascular ultrasound image and an optical coherence tomography image.
A medical image analysis apparatus, the apparatus comprising:
the first acquisition module is used for acquiring angiographic images to be analyzed;
a second acquisition module, configured to obtain a first region of interest in the angiographic image according to the angiographic image;
the first analysis module is used for analyzing the first region of interest to obtain first parameter information corresponding to the first region of interest;
The third acquisition module is used for obtaining an analysis result according to the first parameter information; the analysis result is used for indicating whether the first region of interest meets a preset first condition.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
acquiring an angiographic image to be analyzed;
obtaining a first region of interest in the angiographic image according to the angiographic image;
analyzing the first region of interest to obtain first parameter information corresponding to the first region of interest;
obtaining an analysis result according to the first parameter information; the analysis result is used for indicating whether the first region of interest meets a preset first condition.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring an angiographic image to be analyzed;
obtaining a first region of interest in the angiographic image according to the angiographic image;
analyzing the first region of interest to obtain first parameter information corresponding to the first region of interest;
Obtaining an analysis result according to the first parameter information; the analysis result is used for indicating whether the first region of interest meets a preset first condition.
According to the medical image analysis method, the medical image analysis device, the computer equipment and the storage medium, the first parameter information corresponding to the first region of interest can be obtained by analyzing the first region of interest in the angiographic image to be analyzed, and then the angiographic image to be analyzed can be analyzed according to the first parameter information corresponding to the first region of interest to obtain the analysis result used for indicating whether the first region of interest in the angiographic image to be analyzed meets the preset first condition.
Drawings
FIG. 1 is a diagram of an application environment for a method of medical image analysis in one embodiment;
FIG. 2 is a flow chart of a method of analyzing medical images according to one embodiment;
FIG. 3 is a schematic diagram of a U-Net network in one embodiment;
FIG. 4 is a schematic diagram of a method for calculating blood vessel distribution information within a preset range and blood vessel morphology information within the preset range in a first region of interest according to an embodiment;
FIG. 5 is a schematic diagram of a method of analyzing plaque in a first region of interest in one embodiment;
FIG. 6 is a flow chart of a method of analyzing medical images according to another embodiment;
FIG. 7 is a flow chart of a method of analyzing medical images according to one embodiment;
FIG. 7a is a flow chart of a method of analyzing a medical image according to another embodiment;
FIG. 8 is a diagram of a report format in one embodiment;
fig. 9 is a block diagram showing the structure of a medical image analysis apparatus according to an embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The medical image analysis method provided by the embodiment of the application can be applied to the computer equipment shown in the figure 1. The computer device comprises a processor, a memory, and a computer program stored in the memory, wherein the processor is connected through a system bus, and when executing the computer program, the processor can execute the steps of the method embodiments described below. Optionally, the computer device may further comprise a network interface, a display screen and an input means. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium, which stores an operating system and a computer program, an internal memory. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. Optionally, the computer device may be a server, a personal computer, a personal digital assistant, other terminal devices, such as a tablet computer, a mobile phone, etc., or a cloud or remote server, and the embodiment of the present application does not limit a specific form of the computer device.
In one embodiment, as shown in fig. 2, a medical image analysis method is provided, and the method is applied to the computer device in fig. 1 for illustration, and includes the following steps:
s201, acquiring an angiographic image to be analyzed.
The angiographic image to be analyzed may be a coronary angiographic image or an angiographic image of other parts. Specifically, a computer device acquires an angiographic image to be analyzed. Alternatively, the computer device may acquire the angiographic image to be analyzed from a PACS (Picture Archiving and Communication Systems, image archiving and communication system) server, or may acquire the angiographic image to be analyzed from a corresponding medical imaging device in real time. Optionally, after the computer device obtains the angiographic image to be analyzed, preprocessing may be performed on the angiographic image to be analyzed to remove interference in the angiographic image to be analyzed, where the preprocessing includes resampling, size adjustment, and gray scale normalization.
S202, obtaining a first region of interest in the angiographic image according to the angiographic image.
Specifically, the computer device obtains a first region of interest in the angiographic image from the acquired angiographic image. Optionally, the computer device may obtain the first region of interest in the angiographic image to be analyzed by using a feature detection method, or may input the angiographic image to be analyzed into a preset neural network to obtain the first region of interest in the angiographic image to be analyzed.
S203, analyzing the first region of interest to obtain first parameter information corresponding to the first region of interest.
Specifically, the computer device analyzes a first region of interest in the angiographic image to obtain first parameter information corresponding to the first region of interest. Optionally, the computer device may analyze the position of the first region of interest, analyze the vascular distribution information in a preset range of the first region of interest, analyze the vascular morphology information in the preset range, and analyze the plaque amount of the first region of interest.
S204, according to the first parameter information, obtaining an analysis result; the analysis result is used for indicating whether the first region of interest meets a preset first condition.
Specifically, the computer device obtains an analysis result for indicating whether the first region of interest meets a preset first condition according to the obtained first parameter information. Alternatively, the preset first condition may be whether the first region of interest may be implanted with a bioabsorbable stent (BRS), or whether the first region of interest may be implanted with other medical devices.
According to the medical image analysis method, the first parameter information corresponding to the first region of interest can be obtained by analyzing the first region of interest in the angiographic image to be analyzed, and then the angiographic image to be analyzed can be analyzed according to the first parameter information corresponding to the first region of interest to obtain the analysis result used for indicating whether the first region of interest in the angiographic image to be analyzed meets the preset first condition.
In the above scenario where the first region of interest in the angiographic image is obtained from the angiographic image, in one embodiment, the step S202 includes: the angiographic image (coronary angiographic image) is input into a preset positioning network, and a first region of interest in the angiographic image is obtained through the positioning network.
Specifically, the computer device inputs the angiographic image to be analyzed into a preset positioning network, and a first region of interest in the angiographic image to be analyzed is obtained through the positioning network. Alternatively, the preset positioning network may be a U-Net network as shown in FIG. 3. It will be appreciated that the preset positioning network is a pre-trained positioning network, and optionally, the computer device may train the preset initial positioning network through a plurality of sample angiography images (coronary angiography images) and gold standard images of the region of interest corresponding to the sample angiography images (coronary angiography images) to obtain the positioning network.
In this embodiment, the computer device inputs the angiographic image to be analyzed into a preset positioning network, and because the preset positioning network is a pre-trained network, the first region of interest in the angiographic image to be analyzed can be accurately obtained through the positioning network; in addition, through the preset positioning network, the first region of interest in the angiographic image to be analyzed can be obtained rapidly, so that the efficiency of obtaining the first region of interest in the angiographic image to be analyzed is improved.
Analyzing the first region of interest of the angiographic image to be analyzed to obtain first parameter information corresponding to the first region of interest, and obtaining a scene of an analysis result for indicating whether the first region of interest meets a preset first condition according to the first parameter information, wherein the first parameter information comprises: position information of the first region of interest, blood vessel distribution information within a preset range and blood vessel morphology information within the preset range in the first region of interest, and plaque quantification analysis information of the first region of interest.
Specifically, the first parameter information corresponding to the first region of interest includes: position information of the first region of interest, blood vessel distribution information within a preset range and blood vessel morphology information within the preset range in the first region of interest, and plaque quantification analysis information of the first region of interest. Accordingly, the computer device needs to analyze the position of the first region of interest, analyze the vascular distribution in the preset range of the first region of interest and the vascular morphology in the preset range, and analyze the plaque of the first region of interest, and the above analysis process and the specific process of obtaining the analysis result according to the first parameter information will be described in detail below.
Specifically, analyzing the position of the first region of interest to obtain the position information of the first region of interest may include: and taking an angiographic image to be analyzed and a heat map of the first region of interest as inputs, and transmitting the angiographic image and the heat map of the first region of interest to a trained classification network to obtain the position information of the first region of interest, wherein the trained classification network can be a classical classification network ResNet18 network. Optionally, if the position information of the first region of interest obtained by the computer device is that the first region of interest is located in the left trunk or the coronary artery opening, it is determined that the first region of interest does not meet the preset first condition, or if the position information of the first region of interest obtained by the computer device is that the restenosis/chronic total occlusion lesions in the bridge vascular lesions/Drug Eluting Stent (DES) in the first region of interest, it is determined that the first region of interest does not meet the preset first condition.
Specifically, the analysis of the vessel distribution in the preset range and the vessel morphology in the preset range in the first region of interest is critical in determining the geometric morphology and geometric parameters in the preset range in the first region of interest, including the reference diameters of the two ends of the vessel in the preset range in the first region of interest, whether the vessel is bifurcated, the diameter of the bifurcated vessel, whether and how much the lesion is affected by the branch, the curvature of the lesion vessel, and the length of the lesion area. Optionally, the computer device may obtain the blood vessel distribution information in the preset range and the blood vessel morphology information in the preset range in the first region of interest through a quantitative calculation method as shown in fig. 4, where the process of extracting the blood vessel may include: and constructing a map taking the image gradient of the angiogram as a weight according to a preset range and the angiogram in the given first region of interest, and carrying out vessel segmentation by using map segmentation to extract vessels in the angiogram. The implementation process of the quantitative analysis may include: calculating a blood vessel central line tree according to the blood vessel segmentation result, and then calculating a distribution diagram of the blood vessel diameter along the blood vessel central line tree; calculating the reference diameters and the lesion lengths of blood vessels at two ends of the blood vessels according to the blood vessel diameter distribution diagram, and calculating the main stenosis, the blood vessel reconstruction line, the branch stenosis and the branch diameter; and calculating the curvature of the main blood vessel according to the blood vessel central line tree. If the blood vessel distribution information in the preset range and the blood vessel morphology information in the preset range in the first region of interest obtained by the computer equipment meet the following conditions: the reference diameter of the blood vessel is outside 2.75 mm-3.75 mm; the diameter of the bifurcated lesion vessel is <2.0mm; the diameter of the bifurcated lesion vessel is >2.0mm and the stenosis is >50%; the lesion length is more than or equal to 20mm; the difference between the reference diameters of the proximal end and the distal end is more than 0.25mm; if the blood vessel height is any one of the tortuosity (the blood vessel curvature is larger than the artificially set threshold value), the computer device determines that the first region of interest does not meet the preset first condition.
Specifically, the key of analyzing the plaque of the first region of interest is to determine calcification distribution conditions and plaque components around the first region of interest, optionally, the computer device may analyze the plaque of the first region of interest through an analysis process as shown in fig. 5, optionally, a segmentation network in fig. 5 may be a U-Net network, and a gold standard image when training the segmentation network may be a mark where various plaques in a sample image are located. Optionally, the specific details of the quantitative analysis in fig. 5 are as follows: for calcified areas, calculating the distribution range of the calcified areas around the lumen and the calcified thickness; for lipid and fibrous cap regions, the size was calculated to determine plaque type. If the computer equipment obtains plaque quantification analysis information of the first region of interest, the plaque quantification analysis information of the first region of interest satisfies the following conditions: any one of severe calcification (coverage >270 DEG thickness >500 μm), lipid plaque or calcified plaque, the computer device determines that the above-mentioned first region of interest does not meet the above-mentioned preset first condition.
In this embodiment, the first parameter information corresponding to the first region of interest includes the position information of the first region of interest, the vascular distribution information within the preset range in the first region of interest, the vascular morphology information within the preset range, and the plaque quantization analysis information of the first region of interest, so that the computer device can accurately analyze the first region of interest according to the first parameter information corresponding to the first region of interest, and accuracy of an analysis result obtained by the computer device and used for indicating whether the first region of interest meets the preset first condition is further improved.
In some scenarios, other types of intra-luminal imaging techniques besides angiography may be used to assist in determining the nature of the current lesion, such as intravascular ultrasound (IVUS) and Optical Coherence Tomography (OCT), and in one embodiment, as shown in fig. 6, the method further includes:
s601, acquiring an intracavity image corresponding to an angiographic image.
Specifically, the computer device acquires an intracavity image corresponding to the angiographic image to be analyzed. Alternatively, the intra-luminal image corresponding to the angiographic image to be analyzed may include an intravascular ultrasound image and an optical coherence tomography image. Optionally, the computer device may obtain the intra-cavity image corresponding to the angiographic image to be analyzed from a PACS (Picture Archiving and Communication Systems, image archiving and communication system) server, or may obtain the intra-cavity image corresponding to the angiographic image to be analyzed from a corresponding medical image device in real time.
S602, determining a second region of interest corresponding to the first region of interest in the intra-cavity image.
It will be appreciated that when using an intra-luminal image corresponding to the angiographic image to be analyzed, it is necessary to map the region of interest in the angiographic image with the region of interest in the intra-luminal image to obtain an intra-luminal cross-sectional view of the lesion location. Specifically, the computer device determines a second region of interest corresponding to the first region of interest in the intra-cavity image corresponding to the angiographic image to be analyzed. Optionally, the computer device may determine the second region of interest corresponding to the first region of interest from the intra-cavity images corresponding to the angiographic images by using an image registration method.
S603, analyzing the second region of interest to obtain second parameter information corresponding to the second region of interest.
Specifically, the computer device analyzes a second region of interest in the intra-cavity image corresponding to the angiographic image to obtain second parameter information corresponding to the second region of interest. Optionally, the computer device may analyze the position of the second region of interest, analyze the vascular distribution information in a preset range of the second region of interest, analyze the vascular morphology information in the preset range, and analyze the plaque amount of the second region of interest. Optionally, the second parameter information corresponding to the second region of interest may include: position information of the second region of interest, blood vessel distribution information within a preset range and blood vessel morphology information within the preset range in the second region of interest, and plaque quantification analysis information of the second region of interest. It should be noted that, the specific process of obtaining the second parameter information corresponding to the second region of interest by the computer device may refer to the specific description of obtaining the first parameter information corresponding to the first region of interest in the above embodiment, and this embodiment is not described herein again.
S604, according to the first parameter information and the second parameter information, an analysis result is obtained.
Specifically, the computer device obtains an analysis result for indicating whether the first region of interest meets a preset first condition according to the first parameter information corresponding to the first region of interest and the second parameter information corresponding to the second region of interest. Optionally, if the first parameter information corresponding to the first region of interest and the second parameter information corresponding to the second region of interest obtained by the computer device both meet the conditions described in the foregoing embodiments, the computer device determines that the obtained analysis result indicates that the first region of interest meets the first preset condition; if any one of the first parameter information corresponding to the first interest and the second parameter information corresponding to the second interest, which are obtained by the computer device, does not meet the conditions described in the foregoing embodiments, the computer device determines that the obtained analysis result indicates that the first interest area does not meet the preset first condition.
In this embodiment, the computer device obtains the intra-cavity image corresponding to the angiographic image to be analyzed, and determines the second region of interest corresponding to the first region of interest in the angiographic image to be analyzed in the intra-cavity image, so that the second region of interest can be analyzed to obtain second parameter information corresponding to the second region of interest, and further, according to the first parameter information corresponding to the first region of interest and the second parameter information corresponding to the second region of interest, an analysis result for indicating whether the first region of interest in the angiographic image to be analyzed meets a preset first condition is obtained.
In the above-mentioned scenario in which a second region of interest corresponding to the first region of interest in the angiographic image is determined in the intra-luminal image corresponding to the angiographic image, the computer device may determine the second region of interest according to the vessel diameter distribution map and the vessel topology key point in the angiographic image, and the vessel diameter distribution map and the vessel topology key point in the intra-luminal image, in one embodiment, as shown in fig. 7 and fig. 7a, the step S602 includes:
s701, calculating a first blood vessel diameter distribution map corresponding to the angiographic image and a second blood vessel diameter distribution map corresponding to the intracavity image.
Specifically, the computer device calculates a first vessel diameter distribution map corresponding to the angiographic image and a second vessel diameter distribution map corresponding to the intra-luminal image. Illustratively, the first vessel diameter profile may be obtained by a simple method as exemplified by: the computer equipment calculates the central line of the target blood vessel, then makes the perpendicular line of the central line, and obtains the intersection point position of the perpendicular line and the edge of the blood vessel, thereby obtaining the diameter value of the current central point, and drawing the diameter value of the corresponding central point along the central line according to the physical length of the blood vessel from the near end to the far end, thus obtaining the diameter distribution map. Illustratively, the second vessel diameter map may be obtained by a simple method as exemplified below: the computer equipment firstly obtains all the diameters in the section of each blood vessel, then uses the minimum diameter as the diameter value of the current section position, and draws the diameter value of the corresponding center point along the center line according to the physical length of the blood vessel from the proximal end to the distal end, thus obtaining the diameter distribution map.
S702, calculating a first vessel topological structure key point corresponding to the angiography image and a second vessel topological structure key point corresponding to the intracavity image.
Specifically, the computer device calculates a first vessel topological structure key point corresponding to the angiographic image and a second vessel topological structure key point corresponding to the intracavity image. Alternatively, there are many methods available for extracting key points of the vessel topology, and a simple possible scheme is exemplified here: the first vessel topology key point is extracted, and because it is a two-dimensional image, it can be acquired using intersection detection. The second vessel topological structure key point is extracted, and because the second vessel topological structure key point is the vessel section along the central line, whether the current section is in a bifurcation structure or not can be judged through a simple classification network, so that the topological information is obtained.
S703, determining a second region of interest corresponding to the first region of interest according to the first vessel diameter distribution diagram, the second vessel diameter distribution diagram, the first vessel topological structure key point and the second vessel topological structure key point.
Specifically, the computer device determines a second region of interest corresponding to the first region of interest according to the obtained first vessel diameter distribution map, second vessel diameter distribution map, first vessel topological structure key points and second vessel topological structure key points. Optionally, the computer device may register the first vessel diameter distribution map and the second vessel diameter distribution map, and adjust the first vessel topological structure key point and the second vessel topological structure key point until the first vessel topological structure key point and the second vessel topological structure key point coincide under the condition that the first vessel diameter distribution map and the second vessel diameter distribution map coincide, and map the first region of interest into the intra-cavity image when the first vessel topological structure key point and the second vessel topological structure key point coincide, so as to obtain a second region of interest corresponding to the first region of interest.
In this embodiment, the computer device calculates the first vessel diameter distribution map corresponding to the angiography image and the second vessel diameter distribution map corresponding to the intra-cavity image, so that the second region of interest corresponding to the first region of interest can be accurately determined according to the first vessel diameter distribution map, the second vessel diameter distribution map, the first vessel topology key point and the second vessel topology key point, and the accuracy of the determined second region of interest corresponding to the first region of interest is improved.
In some scenarios, after the computer device obtains an analysis result for indicating whether the first region of interest in the angiographic image meets the preset first condition, in order to intuitively display the analysis result, a user may conveniently view the analysis result, and may display the obtained analysis result in a report format as shown in fig. 8. It should be noted that the report format of fig. 8 is merely an example, and the present embodiment does not limit the report format.
It should be understood that, although the steps in the flowcharts of fig. 2-8 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2-8 may include multiple steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the steps or stages in other steps or other steps.
The application of the degradable stent in coronary artery is still a relatively new application, and the clinician at present mainly depends on experience on whether the degradable stent can be used for patients. A great number of manual measurement operations are also required to measure coronary lesions. This is a high requirement for the clinical experience, qualification and measurement procedures of the doctor. And experience judges that the repeatability and consistency are poor. At present, a complete and mature tool is not available for assisting and supporting doctors to judge the imbeddability of the degradable stent. In order to solve the problems, the proposal in the embodiment of the application realizes the analysis of angiographic images (coronary angiographic images) and is convenient for the subsequent quick and reproducible evaluation of the imbeddability of the coronary degradable stent. The designed working flow reduces the requirement on the experience of doctors, and can obtain relatively comprehensive evaluation results by only executing limited operations, thereby saving the resources of the doctors and simultaneously providing relatively stable services for the patients. The automatic/semi-automatic method allows the measurement results to be reproducible and provides accurate quantitative indicators for the physician for further evaluation.
In one embodiment, as shown in fig. 9, there is provided a medical image analysis apparatus including: the device comprises a first acquisition module, a second acquisition module, a first analysis module and a third acquisition module, wherein:
and the first acquisition module is used for acquiring angiographic images to be analyzed.
And the second acquisition module is used for acquiring a first region of interest in the angiographic image according to the angiographic image.
The first analysis module is used for analyzing the first region of interest to obtain first parameter information corresponding to the first region of interest.
The third acquisition module is used for obtaining an analysis result according to the first parameter information; the analysis result is used for indicating whether the first region of interest meets a preset first condition.
Optionally, the first parameter information includes: position information of the first region of interest, blood vessel distribution information within a preset range and blood vessel morphology information within the preset range in the first region of interest, and plaque quantification analysis information of the first region of interest.
The medical image analysis device provided in this embodiment may execute the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
On the basis of the foregoing embodiment, optionally, the second acquisition module includes: an acquisition unit in which:
the acquisition unit is used for inputting the angiography image into a preset positioning network, and obtaining a first region of interest in the angiography image through the positioning network.
The medical image analysis device provided in this embodiment may execute the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
On the basis of the above embodiment, optionally, the above apparatus further includes: the device comprises a fourth acquisition module, a determination module, a second analysis module and a fifth acquisition module, wherein:
and the fourth acquisition module is used for acquiring the intracavity image corresponding to the angiographic image.
And the determining module is used for determining a second region of interest corresponding to the first region of interest in the intra-cavity image.
The second analysis module is used for analyzing the second region of interest to obtain second parameter information corresponding to the second region of interest.
And the fifth acquisition module is used for obtaining an analysis result according to the first parameter information and the second parameter information.
Optionally, the second parameter information includes: position information of the second region of interest, blood vessel distribution information within a preset range and blood vessel morphology information within the preset range in the second region of interest, and plaque quantification analysis information of the second region of interest.
Alternatively, the intra-luminal image includes an intravascular ultrasound image and an optical coherence tomography image.
The medical image analysis device provided in this embodiment may execute the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
On the basis of the above embodiment, optionally, the determining module includes: a first calculation unit, a second calculation unit, and a determination unit, wherein:
the first calculating unit is used for calculating a first blood vessel diameter distribution map corresponding to the angiography image and a second blood vessel diameter distribution map corresponding to the intracavity image.
The second calculation unit is used for calculating a first vessel topological structure key point corresponding to the angiography image and a second vessel topological structure key point corresponding to the intracavity image.
The determining unit is used for determining a second region of interest corresponding to the first region of interest according to the first vessel diameter distribution diagram, the second vessel diameter distribution diagram, the first vessel topological structure key points and the second vessel topological structure key points.
The medical image analysis device provided in this embodiment may execute the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
For specific limitations of the medical image analysis device, reference may be made to the above limitations of the medical image analysis method, and no further description is given here. The respective modules in the above-described medical image analysis apparatus may be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
acquiring an angiographic image to be analyzed;
obtaining a first region of interest in the angiographic image from the angiographic image;
analyzing the first region of interest to obtain first parameter information corresponding to the first region of interest;
obtaining an analysis result according to the first parameter information; the analysis result is used for indicating whether the first region of interest meets a preset first condition.
The computer device provided in the foregoing embodiments has similar implementation principles and technical effects to those of the foregoing method embodiments, and will not be described herein in detail.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring an angiographic image to be analyzed;
obtaining a first region of interest in the angiographic image from the angiographic image;
analyzing the first region of interest to obtain first parameter information corresponding to the first region of interest;
obtaining an analysis result according to the first parameter information; the analysis result is used for indicating whether the first region of interest meets a preset first condition.
The computer readable storage medium provided in the above embodiment has similar principle and technical effects to those of the above method embodiment, and will not be described herein.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (9)
1. A medical image analysis method, the method comprising:
acquiring an angiographic image to be analyzed;
obtaining a first region of interest in the angiographic image according to the angiographic image;
analyzing the first region of interest to obtain first parameter information corresponding to the first region of interest;
obtaining an analysis result according to the first parameter information; the analysis result is used for indicating whether the first region of interest meets a preset first condition;
The method further comprises the steps of:
acquiring an intracavity image corresponding to the angiographic image;
determining a second region of interest corresponding to the first region of interest in the intra-cavity image;
analyzing the second region of interest to obtain second parameter information corresponding to the second region of interest;
obtaining the analysis result according to the first parameter information and the second parameter information;
and determining a second region of interest corresponding to the first region of interest in the intra-cavity image, including:
calculating a first blood vessel diameter distribution map corresponding to the angiographic image and a second blood vessel diameter distribution map corresponding to the intracavity image;
calculating a first vessel topological structure key point corresponding to the angiography image and a second vessel topological structure key point corresponding to the intracavity image;
determining a second region of interest corresponding to the first region of interest according to the first vessel diameter distribution map, the second vessel diameter distribution map, the first vessel topological structure key point and the second vessel topological structure key point;
determining a second region of interest corresponding to the first region of interest according to the first vessel diameter distribution map, the second vessel diameter distribution map, the first vessel topology key point and the second vessel topology key point, including:
Registering the first vessel diameter profile and the second vessel diameter profile;
adjusting the first vessel topological structure key point and the second vessel topological structure key point under the condition that the first vessel diameter distribution map and the second vessel diameter distribution map are coincident;
and under the condition that the first vessel topological structure key point and the second vessel topological structure key point are overlapped, mapping the first region of interest to the intracavity image to obtain a second region of interest corresponding to the first region of interest.
2. The method of claim 1, wherein obtaining a first region of interest in the angiographic image from the angiographic image comprises:
inputting the angiography image into a preset positioning network, and obtaining a first region of interest in the angiography image through the positioning network.
3. The method according to claim 1 or 2, wherein the first parameter information comprises: the method comprises the steps of determining position information of a first region of interest, vascular distribution information in a preset range in the first region of interest, vascular morphology information in the preset range and plaque quantitative analysis information of the first region of interest.
4. The method of claim 3, wherein the analyzing the first region of interest to obtain the first parameter information corresponding to the first region of interest includes:
inputting the angiography image and the heat map of the first region of interest into a trained classification network to obtain the position information of the first region of interest;
determining blood vessel distribution information in a preset range and blood vessel morphology information in the preset range in the first region of interest by using a quantitative calculation method;
inputting the first region of interest into a segmentation network to obtain plaque quantitative analysis information corresponding to the first region of interest.
5. The method of claim 1, wherein the second parameter information comprises: the position information of the second region of interest, the vascular distribution information within a preset range and the vascular morphology information within the preset range in the second region of interest, and the plaque quantification analysis information of the second region of interest.
6. The method of claim 1, wherein the intra-luminal image comprises an intravascular ultrasound image and an optical coherence tomography image.
7. A medical image analysis device, the device comprising:
the first acquisition module is used for acquiring angiographic images to be analyzed;
a second acquisition module, configured to obtain a first region of interest in the angiographic image according to the angiographic image;
the first analysis module is used for analyzing the first region of interest to obtain first parameter information corresponding to the first region of interest;
the third acquisition module is used for obtaining an analysis result according to the first parameter information; the analysis result is used for indicating whether the first region of interest meets a preset first condition;
a fourth acquisition module, configured to acquire an intra-cavity image corresponding to the angiographic image;
the determining module is used for determining a second region of interest corresponding to the first region of interest in the intra-cavity image;
the second analysis module is used for analyzing the second region of interest to obtain second parameter information corresponding to the second region of interest;
a fifth obtaining module, configured to obtain the analysis result according to the first parameter information and the second parameter information;
The determining module includes:
a first calculation unit for calculating a first blood vessel diameter distribution map corresponding to the angiographic image and a second blood vessel diameter distribution map corresponding to the intracavity image;
the second calculation unit is used for calculating a first vessel topological structure key point corresponding to the angiography image and a second vessel topological structure key point corresponding to the intracavity image;
the determining unit is used for determining a second region of interest corresponding to the first region of interest according to the first vessel diameter distribution diagram, the second vessel diameter distribution diagram, the first vessel topological structure key point and the second vessel topological structure key point;
the determining unit is further configured to register the first vessel diameter profile and the second vessel diameter profile; adjusting the first vessel topological structure key point and the second vessel topological structure key point under the condition that the first vessel diameter distribution map and the second vessel diameter distribution map are coincident; and under the condition that the first vessel topological structure key point and the second vessel topological structure key point are overlapped, mapping the first region of interest to the intracavity image to obtain a second region of interest corresponding to the first region of interest.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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