CN111798432A - Dynamic video image processing method for angiography - Google Patents
Dynamic video image processing method for angiography Download PDFInfo
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- CN111798432A CN111798432A CN202010645139.7A CN202010645139A CN111798432A CN 111798432 A CN111798432 A CN 111798432A CN 202010645139 A CN202010645139 A CN 202010645139A CN 111798432 A CN111798432 A CN 111798432A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
Abstract
The invention discloses a dynamic video image processing method of angiography, belonging to the technical field of medical instruments, comprising the following steps: the method comprises the following steps: analyzing the dynamic video image of the angiography by using a computer image processing technology, and reading the dynamic video of the angiography; step two: performing image normalization and denoising pretreatment on the read video frame image, and segmenting a blood vessel region by using image binarization treatment; step three: calculating fractal dimension of the divided blood vessel region, and calculating the fractal dimension of the blood vessel region by using a differential box dimension calculation method; step four: performing curve fitting on each pixel point of the segmented blood vessel region and the contrast intensity of the pixel point; the method is reasonable in design, and an image imaged by blood vessel parameters and a blood vessel fractal dimension are generated through computer image processing, dimension calculation, curve fitting and parameter imaging technologies to assist a doctor in judging the bleeding point of the arteriole blood vessel in a tissue or at a far end and the complexity of a blood vessel structure.
Description
Technical Field
The invention relates to the technical field of medical instruments, in particular to a dynamic video image processing method for angiography.
Background
Most of the existing methods for judging the bleeding point of the blood vessel are as follows: doctors directly watch the dynamic video images of the angiography through human eyes, the dynamic video images of the angiography are usually about ten seconds, the video time is short, and the doctors sometimes need to repeatedly watch the video images to find out bleeding points of blood vessels. Some points of bleeding in tissue or distal arteriole vessels are sometimes difficult for a physician to visualize.
The medical science finds that by observing a large number of dynamic video images of angiography, the following images are obtained: during contrast agent application, the contrast agent reaches the bleeding point of the blood vessel earlier than the blood vessel region around the bleeding point, and the time for the contrast agent to dissipate is almost the same. This phenomenon indicates that the contrast agent stays longer at the bleeding point of the blood vessel than in the region of the blood vessel surrounding the bleeding point. According to the special phenomenon shown by the blood vessel bleeding point, a dynamic video image of angiography is subjected to computer image processing, dimension calculation, curve fitting and parameter imaging, and then a blood vessel parameter image capable of showing the characteristics of the blood vessel bleeding point and blood vessel dimension are output. The output blood vessel parameter image and the blood vessel dimension can assist a doctor in judging bleeding points of the small artery blood vessels in the tissues or at the far end and the complexity of the blood vessel structure.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
Therefore, an object of the present invention is to provide a dynamic video image processing method for angiography, which can generate an image through vascular parameter imaging and vascular fractal dimension through computer image processing, computational fractal dimension, curve fitting and parametric imaging techniques during the using process, so as to assist a doctor in judging vascular bleeding points in tissues or distal arterioles and the complexity of vascular structures.
To solve the above technical problem, according to an aspect of the present invention, the present invention provides the following technical solutions:
a dynamic video image processing method of angiography comprises the following steps:
the method comprises the following steps: analyzing the dynamic video image of the angiography by using a computer image processing technology, and reading the dynamic video of the angiography;
step two: performing image normalization and denoising pretreatment on the read video frame image, and segmenting a blood vessel region by using image binarization treatment;
step three: calculating fractal dimension of the divided blood vessel region, and calculating the fractal dimension of the blood vessel region by using a differential box dimension calculation method;
step four: performing curve fitting on each pixel point of the segmented blood vessel region and the contrast intensity of the pixel point;
step five: calculating parameter data according to the fitted curve and the selected time region;
step six: outputting a blood vessel parameter image result according to the calculation parameter data;
step seven: and judging the bleeding point of the blood vessel and the complexity of the blood vessel structure according to the blood vessel parameter image and the blood vessel dimension.
As a preferable aspect of the angiographic dynamic video image processing method according to the present invention, the method further includes: step five: the specific steps of calculating the parameter data from the fitted curve and the selected time region are as follows:
1) calculation of area under AUC curve:
2) calculation of time to peak from contrast agent injection:
3) and (3) calculating the rising slope, specifically the speed of the contrast agent peak reaching half of the peak:
4) intensity increment, specifically the calculation of the increase in contrast agent intensity:
5) and (3) calculating the descending slope, specifically, the speed degree of halving the peak value:
6) calculation of time of arrival of contrast at peak:
7) calculation of the mean transit time:
8) fractal dimension of angiographic images.
As a preferable aspect of the angiographic dynamic video image processing method according to the present invention, the method further includes: and respectively generating a color result image of parameter imaging of the angiography region according to the calculated parameter values.
Compared with the prior art, the invention has the beneficial effects that: the angiography dynamic video image processing method is reasonable in structural design, a blood vessel parameter image and a blood vessel dimension division result are generated by analyzing the angiography dynamic video image by using a computer image processing technology, and quantitative research on the dimension division is performed on the blood vessel parameter image and the blood vessel dimension division result so as to assist a doctor in judging bleeding points of arteriole blood vessels in tissues or at a far end and the complexity of blood vessel structures
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail with reference to the accompanying drawings and detailed embodiments, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise. Wherein:
FIG. 1 is a schematic view of the structure of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described herein, and it will be apparent to those of ordinary skill in the art that the present invention may be practiced without departing from the spirit and scope of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Next, the present invention will be described in detail with reference to the drawings, wherein for convenience of illustration, the cross-sectional view of the device structure is not enlarged partially according to the general scale, and the drawings are only examples, which should not limit the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
The invention provides the following technical scheme: a dynamic video image processing method of angiography is characterized in that an image imaged by blood vessel parameters and a blood vessel dimension division result are generated through computer image processing, dimension calculation, curve fitting and parameter imaging technologies, so that a doctor can judge the bleeding point of an arteriole blood vessel in a tissue or at a far end and the complexity of a blood vessel structure;
referring to fig. 1 again, a method for processing an angiographic dynamic video image is characterized in that: the method comprises the following steps:
the method comprises the following steps: analyzing the dynamic video image of the angiography by using a computer image processing technology, and reading the dynamic video of the angiography;
step two: performing image normalization and denoising pretreatment on the read video frame image, and segmenting a blood vessel region by using image binarization treatment;
step three: calculating fractal dimension of the divided blood vessel region, and calculating the fractal dimension of the blood vessel region by using a differential box dimension calculation method;
step four: performing curve fitting on each pixel point of the segmented blood vessel region and the contrast intensity of the pixel point;
step five: calculating parameter data according to the fitted curve and the selected time region;
step six: outputting a blood vessel parameter image result according to the calculation parameter data;
step seven: judging the blood vessel bleeding point and the complexity of the blood vessel structure according to the blood vessel parameter image and the blood vessel dimension;
wherein, the step four: the specific steps of calculating the parameter data from the fitted curve and the selected time region are as follows:
1) calculation of area under AUC curve:
2) calculation of time to peak from contrast agent injection:
3) and (3) calculating the rising slope, specifically the speed degree of the contrast agent peak value halving:
4) intensity increment, specifically the calculation of the increase in contrast agent intensity:
5) calculating the degree of speed of peak halving:
6) calculation of time of arrival of contrast at peak:
7) calculation of the mean transit time:
8) the vessel fractal dimension.
And respectively generating a color result image of parameter imaging of the angiography region according to the calculated parameter values.
During contrast agent application, the contrast agent reaches the bleeding point of the blood vessel earlier than the blood vessel region around the bleeding point, and the time for the contrast agent to dissipate is almost the same. This phenomenon indicates that the contrast agent stays longer at the bleeding point of the blood vessel than in the region of the blood vessel surrounding the bleeding point. According to the special phenomena shown by the blood vessel bleeding points, computer image processing, dimension calculation, curve fitting and parameter imaging technologies are carried out on dynamic video images of angiography to generate an image through blood vessel parameter imaging and a blood vessel dimension division result, and quantitative research on fractal dimension is carried out on the image to assist doctors in judging the complexity of the blood vessel bleeding points of arterioles in tissues or far ends and blood vessel structures.
While the invention has been described above with reference to an embodiment, various modifications may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In particular, the various features of the disclosed embodiments of the invention may be used in any combination, provided that no structural conflict exists, and the combinations are not exhaustively described in this specification merely for the sake of brevity and resource conservation. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (3)
1. A dynamic video image processing method of angiography is characterized in that: the method comprises the following steps:
the method comprises the following steps: analyzing the dynamic video image of the angiography by using a computer image processing technology, and reading the dynamic video of the angiography;
step two: performing image normalization and denoising pretreatment on the read video frame image, and segmenting a blood vessel region by using image binarization treatment;
step three: calculating fractal dimension of the divided blood vessel region, and calculating the fractal dimension of the blood vessel region by using a differential box dimension calculation method;
step four: performing curve fitting on each pixel point of the segmented blood vessel region and the contrast intensity of the pixel point;
step five: calculating parameter data according to the fitted curve and the selected time region;
step six: outputting a blood vessel parameter image result according to the calculation parameter data;
step seven: and judging the bleeding point of the blood vessel and the complexity of the blood vessel structure according to the blood vessel parameter image and the blood vessel dimension.
2. The method as claimed in claim 1, wherein the step five: the specific steps for calculating the following and other relevant curve parameter data from the fitted curve and the selected time region are as follows:
1) calculation of area under AUC curve:
2) calculation of time to peak from contrast agent injection:
3) and (3) calculating the rising slope, specifically the speed of the contrast agent peak reaching half of the peak:
4) intensity increment, specifically the calculation of the increase in contrast agent intensity:
5) and (3) calculating the descending slope, specifically, the speed degree of halving the peak value:
6) calculation of time of arrival of contrast at peak:
7) calculation of the mean transit time:
8) fractal dimension of angiographic images.
3. The method as claimed in claim 1, wherein the method further comprises: and respectively generating a color result image of parameter imaging of the angiography region according to the calculated parameter values.
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