CN114037626A

CN114037626A - Blood vessel imaging method, device, equipment and storage medium

Info

Publication number: CN114037626A
Application number: CN202111266038.XA
Authority: CN
Inventors: 越亮; 冯娟; 江春花
Original assignee: Shanghai United Imaging Healthcare Co Ltd
Current assignee: Shanghai United Imaging Healthcare Co Ltd
Priority date: 2021-10-28
Filing date: 2021-10-28
Publication date: 2022-02-11

Abstract

The embodiment of the invention discloses a blood vessel imaging method, a blood vessel imaging device, blood vessel imaging equipment and a storage medium, wherein the method comprises the following steps: acquiring an original filling image and at least two original mask images of a target acquisition part of a target object; determining an original mask image which is in the same heart beating state with the original filling image from the at least two original mask images as a mask image to be selected; determining a target mask image corresponding to the original filling image according to the mask image to be selected; and determining a blood vessel subtraction image of the target acquisition part according to the original filling image and the target mask image. According to the technical scheme of the embodiment of the invention, the target mask image which is highly matched with the original filling image is determined from the plurality of original mask images, so that the imaging quality of the blood vessel subtraction image is improved.

Description

Blood vessel imaging method, device, equipment and storage medium

Technical Field

The embodiment of the invention relates to the technical field of digital subtraction angiography, in particular to a blood vessel imaging method, a device, equipment and a storage medium.

Background

Digital Subtraction Angiography (DSA) technology is currently well established as a means for diagnosing and treating diseases such as cerebrovascular diseases and cardiovascular diseases. The DSA technology can be used for visually seeing the details of the blood vessels in the region of interest of a subject, and plays a very important role in the operation.

Generally, DSA subtraction technique first performs X-ray photography in a region of interest of a user, fixes a certain frame of image without contrast agent as a mask, then adds contrast agent to obtain a real-time filling image, and finally subtracts the mask from the filling image, so that theoretically an image of only a blood vessel can be obtained. However, because there is a time difference between two captured images, the body of the user tends to move during the time, and whether the body shakes spontaneously or the body moves involuntarily, a large amount of motion artifacts are generated, which affects the subtraction effect.

From the development of the DSA technology to date, some means for reducing motion artifacts are created, and the display effect of blood vessels is improved to a certain extent. However, because the breathing pulsation of the heart causes the motion of the heart and the abdomen of the body to be violent, the recovery effect of the related method for reducing the motion artifact is poor, for example, in the previous research, methods such as elastic registration are often used for complex parts such as the heart, but the calculation amount of the methods such as the elastic registration is extremely large, and the effect of calibrating the motion of the human body in a three-dimensional space on a two-dimensional plane is still limited, and the problem is not solved fundamentally.

Disclosure of Invention

The embodiment of the invention provides a blood vessel imaging method, a blood vessel imaging device, blood vessel imaging equipment and a storage medium, which are used for realizing intelligent subtraction of a blood vessel image.

In a first aspect, an embodiment of the present invention provides a blood vessel imaging method, including:

acquiring an original filling image and at least two original mask images of a target acquisition part of a target object;

determining an original mask image which is in the same heart beating state with the original filling image from the at least two original mask images as a mask image to be selected;

determining a target mask image corresponding to the original filling image according to the mask image to be selected;

and determining a blood vessel subtraction image of the target acquisition part according to the original filling image and the target mask image.

In a second aspect, an embodiment of the present invention further provides a blood vessel imaging apparatus, including:

the image acquisition module is used for acquiring an original filling image and at least two original mask images of a target acquisition part of a target object;

a to-be-selected mask image determining module, configured to determine, from the at least two original mask images, an original mask image in the same heartbeat state as the original filling image as a to-be-selected mask image;

the target mask image determining module is used for determining a target mask image corresponding to the original filling image according to the mask image to be selected;

and the blood vessel subtraction image determining module is used for determining the blood vessel subtraction image of the target acquisition part according to the original filling image and the target mask image.

In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement a vessel imaging method as provided by any of the embodiments of the invention.

In a fourth aspect, the embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the blood vessel imaging method provided by any embodiment of the present invention.

According to the technical scheme of the embodiment of the invention, compared with the existing mode, more original mask image alternatives are provided by acquiring the original filling image and at least two original mask images of the target acquisition part of the target object; then, the original mask image in the same heart beating state with the original filling image in at least two original mask images is taken as a mask image to be selected, so that the influence of motion artifacts generated by the original mask image and the original filling image in the original mask image due to the heart beating on the subtraction effect is effectively reduced; determining a target mask image corresponding to the original filling image according to the mask image to be selected, so that the high matching between the target mask image and the original filling image is ensured; and determining the blood vessel subtraction image of the target acquisition part according to the original filling image and the target mask image, so that the operation cost is low, the processing speed is high, and the imaging quality of the blood vessel subtraction image can be effectively improved.

Drawings

In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, a brief description is given below of the drawings used in describing the embodiments. It should be clear that the described figures are only views of some of the embodiments of the invention to be described, not all, and that for a person skilled in the art, other figures can be derived from these figures without inventive effort.

Fig. 1 is a schematic flow chart of a blood vessel imaging method according to an embodiment of the present invention;

fig. 2 is a schematic flow chart of a blood vessel imaging method according to an embodiment of the present invention;

FIG. 3 is a schematic flow chart of an alternative example of a method for imaging a blood vessel according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of a blood vessel imaging apparatus according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.

It should be further noted that, for the convenience of description, only some but not all of the relevant aspects of the present invention are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.

Fig. 1 is a schematic flow chart of a blood vessel imaging method according to an embodiment of the present invention, which is applicable to a blood vessel visualization system in X-ray sequence imaging, where the method may be executed by a blood vessel imaging device, the device may be implemented by software and/or hardware, and may be configured in a terminal and/or a server to implement the blood vessel imaging method according to the embodiment of the present invention.

As shown in fig. 1, the method of the embodiment may specifically include:

s110, acquiring an original filling image and at least two original mask images of a target acquisition part of the target object.

The target object may be understood as an object to be subjected to subtraction vessel imaging based on the DSA technique. Typically, the target object may be a human or an animal or the like, such as a subject or a patient or the like. The target acquisition site may be a site to be imaged, or a site to be acquired with the original filling image and the original mask image, and is generally a region of interest.

When the heart beats, the blood vessels of the target object may also stretch and relax to some extent as the heart contracts and relaxes. Therefore, as an optional solution of the embodiment of the present invention, the target collection area may include, but is not limited to, a blood vessel of a heart region that is subtracted according to the heart beat, and a blood vessel of a non-heart region that is also subtracted according to the heart beat, such as a head or an extremity.

The original filling image and the original mask image may be obtained by taking an X-ray image of a region of interest of the target object by a digital subtraction angiography technique.

The original filling image may be a unique image left by taking an X-ray of the region of interest of the target object after the contrast agent is added. Where contrast agents are typically chemicals injected (or administered) into tissues or organs to enhance the effect of the observation, these products are either higher or lower density than the surrounding tissue, and the contrast is displayed by some instrument. For example, a commonly used iodine preparation and barium sulfate are observed with X-ray. Because the X-ray cannot penetrate the contrast medium, the purpose of diagnosing the pathological condition of the blood vessel is achieved by utilizing the characteristic that the contrast medium displays an image under the X-ray.

Illustratively, a contrast agent is injected intravenously into the target object, for example, iodine is injected intravenously into the target object, and then an X-ray is taken of the region of interest, in which case the iodine, after entering the blood vessel, passes through the X-ray and leaves a unique image, and the real-time filling image is acquired as the original filling image.

The original mask image is understood to be an image of a frame which is fixed by taking a radiograph of the region of interest of the patient without the addition of a contrast agent. Considering that the target object may move during the X-ray shooting, whether the body shakes spontaneously or the body moves involuntarily, the motion artifact exists in the image, so that the subtraction effect of the mask image and the filling image is affected. Thus, in this embodiment, two or more original mask images may be acquired in preparation for subsequent determination of the original mask image corresponding to the original filling image.

Optionally, under the condition that no contrast agent is added, performing X-ray photography on a region of interest of the target object to obtain two or more original mask images, then adding the contrast agent into the body of the target object, performing X-ray photography on a region having the same pixels as the original mask images, and taking the obtained real-time filling image as the original filling image.

Illustratively, when the detailed condition of a blood vessel in a heart region of a target object needs to be checked, an X-ray film is required to be taken on the heart region of the target object under the condition that a contrast agent is not added, and two or more original mask images are successfully acquired; then, contrast medium is added into the patient with the cardiovascular disease, X-ray film shooting is carried out on the heart area of the patient with the cardiovascular disease, and after the contrast medium is irradiated by X-ray, a unique image is left, so that a real-time filling image of the patient with the cardiovascular disease is obtained, namely an original filling image of the heart area of the patient with the cardiovascular disease is obtained.

Alternatively, the original filling image and the at least two original mask images of the target capturing portion of the target object may be obtained by first obtaining a plurality of original mask images of the target capturing portion of the target object and then obtaining the original filling image of the target capturing portion. The acquiring of the multiple original mask images of the target acquisition part of the target object may be acquiring of multiple original mask images in one cardiac cycle, or acquiring of multiple original mask images in two or more cardiac cycles. In consideration of the individual difference of the target object and the difference of the device performance, the acquisition sequence for acquiring the original mask image and the original filling image may be determined according to the actual requirement, and is not particularly limited herein.

And S120, determining the original mask image which is in the same heart beating state with the original filling image from the at least two original mask images as a mask image to be selected.

A beating state is understood to be the state of the heart accompanying its systolic and diastolic movements. In the embodiment of the present invention, specifically, the cardiac motion information may be divided into at least two beating states according to the degree of contraction and the degree of diastole of the heart by taking each cardiac cycle as a unit; or, determining a systolic period and a diastolic period of the heart in each cardiac cycle, and dividing the cardiac motion information into at least two cardiac beat states according to a total systolic duration and a total diastolic duration corresponding to the systolic period and the diastolic period of the heart, respectively, for example, specifically, dividing the total systolic duration and the total diastolic duration according to a preset fixed duration to obtain a plurality of divided time periods, and using the cardiac motion information in each divided time period as a uniform cardiac beat state, in other words, each time period may correspond to one cardiac beat state; still alternatively, at least two heart beat states may be partitioned according to a range of amplitude fluctuations of the heart beat waveform for each cardiac cycle.

The mask image to be selected may be an original mask image in the same beating state of the heart as the original filling image. It can be understood that, in practical applications, the number of the determined mask images to be selected may be one or two or more, depending on the image acquisition parameters.

Optionally, it is determined whether the original mask image and the original filling image are in the same beating state of the heart according to the acquired time information of the original mask image and the acquired time information of the original filling image.

Optionally, according to the original filling image, the image acquisition frequency of the original mask image and the cardiac cycle of the target object, the original mask image in the same heart beating state as the original filling image is determined from the at least two original mask images and is used as a mask image to be selected.

Optionally, it is determined whether the original mask image and the original filling image are in the same beating state of the heart through the similarity between the original mask image and the original filling image. Wherein the similarity between the original mask image and the original filling image can be determined by at least one of a pearson correlation coefficient method, a cross-correlation coefficient method, and a maximum subtraction histogram energy method.

Optionally, when the original mask image and the original filling image are acquired, the physiological signal of the target object is acquired in real time, and then whether the original mask image and the original filling image are in the same heartbeat state is determined according to the physiological signal corresponding to the original mask image and the original filling image. The physiological signal can be at least one of electroencephalogram signal, electrocardiosignal, pulse signal or signal extracted by other mode images.

In addition, the original mask image in the same heart beating state with the original filling image can be determined through the low-frequency information of one original mask image in the original mask images and the average high-frequency information of the original mask images. Or, performing iterative processing on the plurality of original mask images, for example, selecting image information of a preset proportion in each original mask image for processing, so as to determine the original mask image in the same heartbeat state as the original filling image.

Optionally, before determining, from the at least two original mask images, an original mask image in the same heartbeat state as the original filling image as a mask image to be selected, the original filling image and the at least two original mask images may be preprocessed, and then, determining, from the at least two preprocessed original mask images, an original mask image in the same heartbeat state as the preprocessed original filling image as a mask image to be selected, so as to prepare for subsequently determining a target mask image. Before determining an original mask image in the same heart beating state with an original filling image from at least two original mask images as a mask image to be selected, respectively preprocessing the original filling image and the at least two original mask images, wherein the number of the preprocessed images is relatively large; the advantage of this is that the original mask image after screening can be obtained, and a more accurate selection range is provided for later selecting the original mask image in the same beating state of the heart as the original filling image.

Optionally, after the original mask image in the same beating state as the original filling image is determined from the at least two original mask images as a mask image to be selected, the original filling image and the mask image to be selected are preprocessed. So as to determine the target mask image in the following.

Of course, the two preprocessing occasions may also be combined, before the original mask image in the same heart beating state as the original filling image is determined from the at least two original mask images as the mask image to be selected, the original filling image and the at least two original mask images are preprocessed, and after the original mask image in the same heart beating state as the original filling image is determined from the at least two original mask images as the mask image to be selected, the original filling image and the mask image to be selected are preprocessed. After determining the original mask image in the same beating state as the original filling image from the at least two original mask images as the mask image to be selected, respectively preprocessing the original mask image and the mask image to be selected, which has the advantage that the number of preprocessed images is relatively small, and the target mask image corresponding to the original filling image can be determined from the two or more mask images to be selected.

The preprocessing can be understood as an operation of initializing the original mask image and the original filling image, so as to enable the original mask image and the original filling image to be better matched. Illustratively, the preprocessing may be to perform logarithm (also called Log transform) and/or noise reduction on the image. The noise reduction mode may be multi-scale noise reduction, etc.

Specifically, the preprocessing the original filling image and the at least two original mask images respectively may include: and respectively carrying out logarithmic transformation processing on the original filling image and the at least two original mask images, and respectively carrying out filtering processing on the original filling image and the at least two original mask images after the logarithmic transformation processing.

Because the X-ray shows the energy distribution of exponential decay, the distribution information of each result can be reflected more clearly through log transformation; the second step is noise reduction, the X-ray itself has a lot of noise, including impulse noise, gaussian noise, etc., the purpose of noise reduction is to make the original mask image and the original filling image more accurately de-matched, and for example, at least one of the filtering modes, such as mean filtering, gaussian filtering, bilateral filtering, and trilateral filtering, may be adopted.

Specifically, adaptive trilateral filtering may be employed to denoise the original mask image and the original filling image to better preserve image edge information. The inventor finds that, in the process of implementing the present invention, bilateral filtering considers a distribution condition of a gray value and a space of an image itself, that is, the closer the distance, the greater the weight, and although the noise removing effect is good, the corresponding spatial structure information can be removed, because the technical solution of the embodiment of the present invention adds a third weight information, that is, a pulse weight, and the definition of the pulse weight is to firstly determine whether the point is an edge point of the image, and if the point is an edge point and a signal of the edge point is a pulse signal, a bilateral filtering coefficient can be increased at this time, so as to implement a better denoising capability.

It should be noted that, the original filling image and the at least two original mask images may be filtered first, and then the filtered original filling image and the at least two original mask images may be subjected to logarithmic transformation.

And S130, determining a target mask image corresponding to the original filling image according to the mask image to be selected.

The target mask image can be understood as a mask image to be selected which is determined from the mask to be selected and is more matched with the original filling image. It will be appreciated that the number of original mask images determined from the at least two original mask images to be in the same beating state as the original filling image may be one, two or more, i.e. the number of determined mask images to be selected may be one, two or more. At this time, the mode of determining the target mask image may specifically be that, when the number of the determined mask images to be selected is one, the mask image to be selected is taken as the target mask image corresponding to the original filling image; and when the number of the determined mask images to be selected is two or more, determining the mask image to be selected corresponding to the original filling image from the two or more mask images to be selected.

The method includes the steps that a to-be-selected mask image corresponding to an original filling image is determined from two or more to-be-selected mask images, wherein the to-be-selected mask image corresponding to the original filling image is selected from one of the two or more to-be-selected mask images, or an image with few image artifacts is selected from the two or more to-be-selected mask images to serve as the to-be-selected mask image corresponding to the original filling image, or the to-be-selected mask image corresponding to the original filling image is determined from the two or more to-be-selected mask images according to the image acquisition time of each to-be-selected mask image, the acquisition time of the original filling image and the cardiac cycle.

And S140, determining a blood vessel subtraction image of the target acquisition part according to the original filling image and the target mask image.

The blood vessel subtraction image can be obtained by subtracting the target mask image from the original filling image, and the blood vessel subtraction image of only the blood vessel can be obtained after the subtraction of the two images;

specifically, a superposed part of the original filling image and the target mask image is identified, and the superposed part can be understood as all information in the target mask image; and subtracting the part corresponding to the target mask image in the original filling image, so that the blood vessel added with the contrast agent in the original filling image can be avoided, and a blood vessel subtraction image of only the blood vessel is obtained.

After the determining the blood vessel subtraction image of the target acquisition site according to the original filling image and the target mask image, further comprising: and carrying out image post-processing on the blood vessel subtraction image to obtain a target blood vessel image. The post-processing method for the image may be various, and may include at least one of the processes of removing noise, reducing motion artifacts, stretching, shrinking, and enhancing on the blood vessel subtraction image. For example, the stretching process or the shrinking process may be performed for different gray scale ranges of the blood vessel subtraction image by an S-shaped curve. The advantage of this operation is that the blood vessel contrast in the blood vessel subtraction image can be improved by performing image post-processing on the blood vessel subtraction image, and the subtraction effect of the blood vessel subtraction image is optimized.

Optionally, the vessel subtraction image is stretched based on a color lookup table curve to obtain a target vessel image.

The color lookup table curve is also called as an LUT curve, and the LUT curve can be used to stretch the image to more prominently display the blood vessel image. The LUT may be a mapping table of pixel gray values. Specifically, the gray value of the pixel of the blood vessel subtraction image is subjected to a certain transformation, such as threshold, inversion, binarization, contrast adjustment, linear transformation, and the like, to obtain another gray value corresponding to the gray value of the pixel of the blood vessel subtraction image. The above operation may serve to highlight useful information in the vessel subtraction image and enhance the light contrast of the vessel subtraction image.

Optionally, after performing stretching processing on the blood vessel subtraction image based on the color lookup table curve, the method may further include: and performing image enhancement processing on the stretched blood vessel subtraction image. And then the blood vessel subtraction image after the image enhancement processing is taken as a target blood vessel image.

Image enhancement is understood to be a method which uses an image pyramid in order to interpret an image with multiple resolutions. The image pyramid comprises a Gaussian pyramid, a Laplacian pyramid and the like, and the display quality of the image can be improved through the image pyramid, so that the extraction and the identification of information are facilitated. For example, the information which is considered unnecessary or interfered is selected to be removed, and the required information is highlighted, thereby being beneficial to the analysis and interpretation of the image or the further processing.

According to the technical scheme of the embodiment, compared with the prior art, more original mask image alternatives are provided by acquiring the original filling image and at least two original mask images of the target acquisition part of the target object; then, the original mask image in the same heart beating state with the original filling image in at least two original mask images is taken as a mask image to be selected, so that the influence of motion artifacts generated by the original mask image and the original filling image in the original mask image due to the heart beating on the subtraction effect is effectively reduced; determining a target mask image corresponding to the original filling image according to the mask image to be selected, so that the high matching between the target mask image and the original filling image is ensured; and determining the blood vessel subtraction image of the target acquisition part according to the original filling image and the target mask image, so that the operation cost is low, the processing speed is high, and the imaging quality of the blood vessel subtraction image can be effectively improved.

Fig. 2 is a schematic flow chart of another blood vessel imaging method according to an embodiment of the present invention, where on the basis of any optional technical solution in the embodiment of the present invention, optionally, the determining, from the at least two original mask images, an original mask image in the same beating state as the original filling image as a mask image to be selected includes: determining the image acquisition frequency of an original filling image and each original mask image and the cardiac cycle of a target object; and according to the cardiac cycle and the image acquisition frequency, determining an original mask image which is in the same heart beating state with the original filling image from at least two original mask images as a mask image to be selected.

On the basis of any optional technical scheme of the present invention, optionally, the determining, according to the mask image to be selected, a target mask image corresponding to the original filling image includes: if the number of the determined mask images to be selected is two or more, determining a target mask image corresponding to the original filling image from the two or more mask images to be selected based on a preset judging method;

on the basis of any optional technical solution of the present invention, optionally, the determining a blood vessel subtraction image of the target acquisition site according to the original filling image and the target mask image includes: and carrying out rigid registration on the original filling image and the target mask image, and subtracting the registered original filling image and the target mask image to obtain a blood vessel subtraction image of the target acquisition part.

The technical terms and the technical features that are the same as those in the previous embodiment are not described in detail in this embodiment.

As shown in fig. 2, the method of the embodiment may specifically include:

s210, acquiring an original filling image and at least two original mask images of a target acquisition part of the target object.

S220, determining the image acquisition frequency of the original filling image and the original mask image and the cardiac cycle of the target object.

The image capturing frequency may be understood as the number of images that can be captured per unit time. The image acquisition frequency of the original filling image and the image acquisition frequency of the original mask image may be the same or different. In the embodiment of the present invention, the image capturing frequency may be set according to actual requirements, and is not specifically limited herein. Typically, the image acquisition frequency is set prior to acquiring the original filling image and the original mask image.

Wherein the cardiac cycle is understood as the process that the cardiovascular system undergoes from the start of one heart beat to the start of the next heart beat. In particular, each contraction and relaxation of the heart constitutes a cardiac cycle. Specifically, the change of the intraventricular pressure, the ventricular volume, the blood flow and the valve activity in each phase of the cardiac cycle, for example, the relaxation activity of the ventricles is taken as the center, and the whole cardiac cycle moves according to eight phases. The eight phases may be isovolumetric systolic, rapid ejection, slow ejection, pre-diastole, isovolumetric diastolic, rapid filling, slow filling and atrial systolic.

In the embodiment of the present disclosure, each phase in each cardiac cycle can be regarded as one heart beat state, i.e., eight heart beat states can be divided in each cardiac cycle. Of course, two adjacent time phases may be set to be in a uniform jitter state. And then, judging whether the original mask image and the original filling image are in the same heart beating state or not by determining whether the original mask image and the original filling image are in the same time phase or not.

Wherein the time elapsed for one cardiac cycle is determined by the heart rate. The heart rate is an important index reflecting the health degree of cardiovascular functions of human bodies. If the heart rate is 75 beats/minute, the elapsed time to complete a cardiac cycle is 0.8 seconds.

Specifically, obtaining the heart rate value can be realized by detection technologies such as a heart beat recognition technology of a microblog radar, a heart beat recognition technology of image capture, a heart beat recognition technology of a visual image and the like.

The heart beat identification technology of the microwave radar can be that the microwave radar is used for collecting heart beat signals and dividing a periodic signal sequence into discrete frames; and then extracting the heartbeat by utilizing technologies such as signal processing and the like to obtain a heart rate value.

The heart beat recognition technology of image capture can be understood as a heart rate measurement method based on image capture, and a feature vector T of a detection space and a threshold epsilon for converting into a binary image are obtained; obtaining a video of heart rate detection; extracting each frame image F1, F2, … and Fx from the video; obtaining a gray scale map Gx of the Fx in the detection space; obtaining a gray scale image Ry which is different from G1 according to Gx; extracting a change area My of each blood vessel image; extracting a value Ky of a change area in the image; extracting a changed characteristic value from the change Ky to obtain a period Tr; a heart rate value HR is obtained.

The heart beating recognition technology of the visual image can be understood as a human face video non-contact real-time heart rate measurement system based on LabVIEW. Capturing a face image through a common camera, carrying out 3-primary color separation on each frame of image to generate three-channel images of R (red), G (green) and B (blue), identifying the face through a skin color model, determining an ROI (region of interest) of the face, extracting the mean value of a G channel, eliminating baseline drift of signals and peak detection of the signals by combining wavelet transformation, and finally obtaining a measured heart rate value.

It should be noted that, in a short time without violent movement, the cardiac cycle is a relatively stable cycle change, and the image acquisition frequencies of the original filling image and each original mask image and the cardiac cycle of the target object can be determined by combining the image acquisition frequencies of the original filling image and each original mask image.

And S230, according to the cardiac cycle and the image acquisition frequency, determining an original mask image which is in the same heart beating state with the original filling image from the at least two original mask images as a mask image to be selected.

As described above, different heart beating states can be divided in each cardiac cycle, the image acquisition time of the original filling image and each original mask image can be respectively determined according to the image acquisition frequency of the original filling image and the original mask image, and further, the heart beating state corresponding to the original filling image is determined according to the image acquisition time of the original filling image and the time range corresponding to each heart beating state in each cardiac cycle; and then, according to the image acquisition time of each original mask image and the time range corresponding to each heart beating state in each cardiac cycle, respectively determining the heart beating state corresponding to each original filling image, and further determining the original mask image in the same heart beating state with the original filling image.

It should be noted that, if the original mask image in the same beating state as the original filling image is not determined based on the preset rule, the original mask image whose image acquisition time is closest to the time period corresponding to the beating state of the heart in which the original filling image is located may be used as the mask image to be selected. Specifically, the target time period corresponding to the heart beating state in each cardiac cycle, which is the same as the heart beating state in which the original filling image is located, can be respectively determined; and calculating the absolute value of the time difference between the time endpoints of the image acquisition time of each original mask image in the cardiac cycle to which the image acquisition time belongs and the time endpoints of the image acquisition time of the adjacent original mask image in the target time period corresponding to the cardiac cycle, and taking the original mask image corresponding to the minimum absolute value in the calculated absolute values as the original mask image in the same heart beating state with the original filling image, namely as the mask image to be selected.

S240, if the number of the determined mask images to be selected is two or more, determining a target mask image corresponding to the original filling image from the two or more mask images to be selected based on a preset judging method.

The preset judging method comprises at least one of a Pearson correlation coefficient method, a cross-correlation coefficient method and a maximum subtraction histogram energy method.

The pearson correlation coefficient method is understood to be a method of calculating a straight-line correlation. The Pearson correlation coefficient can reflect the linear correlation degree between two random variables, so that the Pearson correlation degree between the two variables can be judged by utilizing the Pearson correlation coefficient; the pearson correlation is also called product-difference correlation or matrix correlation. The pearson correlation coefficient can be realized by Matlab, and specifically, when the variables in the two images are linearly correlated, the pearson correlation coefficient can show the linear correlation degree of the two images, that is, the absolute value of the pearson correlation coefficient is large, which indicates that the correlation is strong; the absolute value of the pearson correlation coefficient is small, indicating that the correlation is weak.

For example, when two or more mask images to be selected are determined, a target mask image corresponding to the original filling image can be determined from the two or more mask images to be selected based on a pearson correlation coefficient method; specifically, the pearson correlation coefficient method is used for respectively calculating the pearson correlation coefficient absolute values of variables in the original filling image and each to-be-selected mask image so as to determine the correlation between the to-be-selected mask image and the original filling image, and the to-be-selected mask image with the strongest correlation with the original filling image is used as the target mask image. In order to ensure accurate determination of the determination, further, a scatter diagram of the original filling image and the mask image to be selected can be drawn, that is, the correlation degree of the original filling image and the mask image to be selected is analyzed by using the pearson correlation coefficient absolute value and the scatter diagram together.

The cross correlation coefficient method may be a method of studying the degree of linear correlation between variables. The cross correlation coefficient method is based on gaussian distribution, and can use cross correlation coefficient or mutual information as the basis for analyzing the linear correlation degree between variables, wherein the cross correlation coefficient and the mutual information are equivalent, and a conversion formula exists between the cross correlation coefficient and the mutual information. Specifically, when the cross-correlation coefficient between two variables is zero, it indicates that the two variables are independent of each other and mutual information is 0; when the cross-correlation coefficient is + -1 \ pm1 + -1, it indicates that the two variables are completely correlated and the mutual information is infinite.

For example, when the determined mask images to be selected are two or more, the target mask image corresponding to the original filling image may be determined from the two or more mask images to be selected based on a cross-correlation coefficient method. Specifically, the cross-correlation coefficient of the variables in the original filling image and each to-be-selected mask image is calculated by using a cross-correlation coefficient method, and then the to-be-selected mask image most related to the original filling image is determined as the target mask image according to the cross-correlation coefficient.

The maximum subtraction histogram energy method is also called gray level histogram comparison, and is a simple and practical method. Specifically, the gray histogram may be understood as an image obtained by counting gray level distributions in an image through a function of the gray level distributions; by checking the distribution condition of the image gray level histogram, the frequency of certain gray level in the image can be intuitively known. Specifically, the obtaining of the gray level histogram of the image may be implemented by any one of Matlab, Opencv, and Python.

For example, when the determined mask images to be selected are two or more, the target mask image corresponding to the original filling image can be determined from the two or more mask images to be selected based on the maximum subtraction histogram energy method. Specifically, the maximum subtraction histograms of the original filling image and each to-be-selected mask image are respectively determined, the histogram overlap ratio of the original filling image and each to-be-selected mask image is respectively calculated, and then the target mask image corresponding to the original filling image is determined according to the histogram overlap ratio.

Because the original filling image and the to-be-selected mask image are in a relatively close heart state, and only the original filling image has more blood vessel images compared with the to-be-selected mask image, when the original filling image and the to-be-selected mask image are converted into the histogram, the original filling image and the to-be-selected mask image are extremely close to each other, and only the original filling image has more blood vessel information compared with the to-be-selected mask image, the correlation between the original filling image and the to-be-selected mask image can be identified by the method.

It should be noted that the target mask image corresponding to the original filling image may be determined by one of the pearson correlation coefficient method, the cross-correlation coefficient method, and the maximum subtraction histogram energy method, or two or more methods may be used to determine the effect of the target mask image corresponding to the original filling image in combination.

S250, carrying out rigid registration on the original filling image and the target mask image, and subtracting the registered original filling image and the target mask image to obtain a blood vessel subtraction image of the target acquisition part.

Rigid registration is understood to mean the process in which the physical properties of the two images are not changed, but are changed in spatial position and attitude to align the two images. Specifically, in the rigid registration process, an optimal set of rotation and translation matrices can be obtained through calculation, and the original filling image is aligned with the target mask image.

Optionally, rigid registration of the original filling image and the target mask image is realized by means of pixel displacement.

Alternatively, the rigid registration can also be realized by a registration algorithm, which mainly includes the following: ICP (most recent iteration Point matching algorithm) and its variants, NDT (normal distribution transform), Super4CS, Deep Learning (Deep Learning based approach), Deep Closest Point, Deep ICP.

Exemplarily, firstly, feature extraction is carried out on two images, namely an original filling image and a target mask image, so as to obtain respective feature points of the original filling image and the target mask image; similarity measurement is carried out on the original filling image and the target mask image, and matched feature point pairs are found; then obtaining space coordinate transformation parameters of the original filling image and the target mask image through the matched characteristic point pairs; and finally, carrying out rigid registration on the images according to the coordinate transformation parameters of the original filling image and the target mask image.

Wherein the original filling image and the target mask image are in rigid registration, which has important application value in clinical medicine. Specifically, certain organs in the human body are basically not deformed within a certain image acquisition time interval, such as the brain and the like; there are also some organs that move autonomously in corresponding time intervals to generate internal distortions, such as the lung and heart, which cause differences in shape, size, etc. of the acquired images, whether filling images or mask images, at different times, resulting in differences in the choice of registration methods for the medical images of different organs. Therefore, when images acquired from different parts of the human body are aligned, a method corresponding to the features of the parts is adopted, and the method can be a rigid registration method or a non-rigid registration method, which is not limited herein.

According to the technical scheme of the embodiment, the original mask image in the same heart beating state with the original filling image is determined from at least two original mask images as the mask image to be selected according to the image acquisition frequency of the original filling image and each original mask image and the cardiac cycle of the target object, the periodic characteristic of the heart beating is fully considered, the original mask image corresponding to the original filling image is preliminarily selected, and then when the determined mask image to be selected is two or more than two, the mask image to be selected is screened again based on a preset discrimination method, the target mask image corresponding to the original filling image is determined, the accurate screening of the original mask image is realized, and the matching degree of the target mask image and the original filling image is effectively ensured; and after the original filling image and the target mask image are subjected to rigid registration, the original filling image and the target mask image are subtracted to obtain a blood vessel subtraction image of the target acquisition part, so that the technical effect of further improving the image subtraction quality is achieved.

Fig. 3 is a schematic flowchart of a vessel imaging method in an application scenario according to an embodiment of the present invention; in order to further clarify the technical solution of the embodiment of the present invention for those skilled in the art, a specific application scenario is given below by taking an example that a researcher takes an X-ray photograph of a cardiac region of a subject to obtain a subtraction image of a blood vessel thereof.

The method of the embodiment of the invention can comprise the following steps:

firstly, a plurality of original mask images of a target object are acquired through a DSA technology, then, after a contrast agent is used for the target object, an original filling image of a target acquisition part is acquired, in order to improve the image quality and ensure the matching accuracy, the acquired original mask images and the acquired original filling images can be preprocessed in an image preprocessing mode, and the preprocessed original mask images and the preprocessed original filling images are obtained. The image preprocessing method may be Log transformation, multi-scale noise reduction, and the like.

Then, for the preprocessed original mask image and the preprocessed original filling image, the original mask image in the same heart beating state as the original filling image is intelligently recognized by using a heart beating recognition technology as a mask image to be selected, and then the mask image to be selected which is most matched with the original filling image is further determined as a target mask image according to the mask image to be selected.

Further, the target mask image may be subjected to image correction by an image correction technique such as pixel shift with reference to the original filling image so as to align the target mask image with the original filling image. And then, subtracting the original filling image and the corrected target mask image to obtain a blood vessel subtraction image of the target acquisition part.

Finally, the blood vessel subtraction image can be subjected to image post-processing by a preset image post-processing mode, for example, the image is stretched by using an LUT curve to more prominently display the blood vessel image; and the second step is to enhance the image, and specifically, the image enhancement can be performed by adopting a Gaussian pyramid and a Laplacian pyramid, so that the display effect of the blood vessels in the blood vessel subtraction image is further improved.

According to the technical scheme of the embodiment, the original mask image which is the best image of the original filling image can be accurately acquired by combining the heart beat recognition technology with the DSA technology, and then the high-quality image subtraction effect can be realized by combining the image preprocessing, the pixel shifting and the image post-processing modes, so that the imaging quality of the blood vessel subtraction image can be comprehensively improved in multiple angles.

Fig. 4 is a schematic structural diagram of a blood vessel imaging apparatus according to an embodiment of the present invention, which may perform the blood vessel imaging method according to the above embodiment, and the apparatus may include: a picture acquisition module 410, a candidate mask image determination module 420, a target mask image determination module 430 and a vessel subtraction image determination module 440.

The image acquisition module 410 is configured to acquire an original filling image and at least two original mask images of a target acquisition portion of a target object; a to-be-selected mask image determining module 420, configured to determine, from the at least two original mask images, an original mask image in the same heartbeat state as the original filling image as a to-be-selected mask image; a target mask image determining module 430, configured to determine a target mask image corresponding to the original filling image according to the mask image to be selected; a blood vessel subtraction image determining module 440, configured to determine a blood vessel subtraction image of the target acquisition location according to the original filling image and the target mask image.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the to-be-selected mask image determination module is configured to:

determining an image acquisition frequency of the original filling image and each of the original mask images and a cardiac cycle of the target subject;

and according to the cardiac cycle and the image acquisition frequency, determining an original mask image which is in the same heart beating state with the original filling image from the at least two original mask images as a mask image to be selected.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the target mask image determination module is configured to:

and if the number of the determined mask images to be selected is two or more, determining a target mask image corresponding to the original filling image from the two or more mask images to be selected based on a preset judging method.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the blood vessel imaging apparatus further includes: the image updating device comprises an image preprocessing module and an image updating module.

The image preprocessing module is used for preprocessing the original filling image and the at least two original mask images respectively before determining the original mask image in the same heart beating state with the original filling image from the at least two original mask images as a mask image to be selected; and the image updating module is used for respectively updating the original filling image and the at least two original mask images according to the preprocessed result.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the image preprocessing module is configured to:

and respectively carrying out logarithmic transformation processing on the original mask image and the at least two original filling images, and respectively carrying out filtering processing on the original mask image and the at least two original filling images after the logarithmic transformation processing.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the vessel subtraction image determining module is configured to:

and carrying out rigid registration on the original filling image and the target mask image, and subtracting the registered original filling image and the target mask image to obtain a blood vessel subtraction image of the target acquisition part.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the blood vessel imaging apparatus further includes:

and the image enhancement processing module is used for stretching the blood vessel subtraction image based on a color lookup table curve after the blood vessel subtraction image of the target acquisition part is determined according to the original filling image and the target mask image, and performing image enhancement processing on the stretched blood vessel subtraction image to obtain a target blood vessel image.

The blood vessel imaging device can execute the blood vessel imaging method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the executed blood vessel imaging method.

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. FIG. 5 illustrates a block diagram of an exemplary electronic device 12 suitable for use in implementing embodiments of the present invention. The electronic device 12 shown in fig. 5 is only an example and should not bring any limitation to the function and the scope of use of the embodiment of the present invention.

As shown in FIG. 5, electronic device 12 is embodied in the form of a general purpose computing device. The components of electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.

Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

Electronic device 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by electronic device 12 and includes both volatile and nonvolatile media, removable and non-removable media.

The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, and commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.

A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.

Electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with electronic device 12, and/or with any devices (e.g., network card, modem, etc.) that enable electronic device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, the electronic device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet) via the network adapter 20. As shown in FIG. 5, the network adapter 20 communicates with the other modules of the electronic device 12 via the bus 18. It should be appreciated that although not shown in FIG. 5, other hardware and/or software modules may be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, to implement a blood vessel imaging method provided by the present embodiment.

Embodiments of the present invention also provide a storage medium containing computer-executable instructions which, when executed by a computer processor, perform a method of vessel imaging, the method comprising: acquiring an original filling image and at least two original mask images of a target acquisition part of a target object; determining an original mask image which is in the same heart beating state with the original filling image from the at least two original mask images as a mask image to be selected; determining a target mask image corresponding to the original filling image according to the mask image to be selected; and determining a blood vessel subtraction image of the target acquisition part according to the original filling image and the target mask image.

Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for carrying out operations for embodiments of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method of imaging a blood vessel, comprising:

2. The method according to claim 1, wherein the determining, as the mask image to be selected, an original mask image in a beating state of the heart as the original filling image from the at least two original mask images comprises:

determining image acquisition frequencies of the original filling image and the original mask image and a cardiac cycle of the target subject;

3. The method according to claim 1, wherein the determining a target mask image corresponding to the original filling image from the mask image to be selected comprises:

4. The method according to claim 1, before said determining an original mask image in the same beating state as the original filling image from the at least two original mask images as a candidate mask image, further comprising:

and respectively preprocessing the original filling image and the at least two original mask images, and respectively updating the original filling image and the at least two original mask images according to the preprocessed result.

5. The method according to claim 4, wherein the pre-processing the original mask image and the at least two original filling images separately comprises:

and respectively carrying out logarithmic transformation processing on the original filling image and the at least two original mask images, and respectively carrying out filtering processing on the original filling image and the at least two original mask images after the logarithmic transformation processing.

6. The method of claim 1, wherein determining a vessel subtraction image of the target acquisition site from the original filling image and the target mask image comprises:

7. The method of claim 1, further comprising, after said determining a vessel subtraction image of the target acquisition site from the original filling image and the target mask image:

and stretching the blood vessel subtraction image based on the color lookup table curve to obtain a target blood vessel image.

8. A method apparatus for imaging a blood vessel, comprising:

9. An electronic device, characterized in that the electronic device comprises:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement the vessel imaging method of any of claims 1-7.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the vessel imaging method as set forth in any one of claims 1-7.