CN112669449A - CAG and IVUS accurate linkage analysis method and system based on 3D reconstruction technology - Google Patents
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Abstract
The invention discloses a CAG and IVUS precise linkage analysis method and a system based on a 3D reconstruction technology, which comprises the following steps: respectively selecting a single contrast image with a clear IVUS guide wire track from two contrast image sequences under different contrast visual angles, and performing image preprocessing; carrying out interactive segmentation extraction on the IVUS guide wire in the single preprocessed contrast image, and extracting two-dimensional track coordinates of the IVUS guide wire from the two images respectively; performing discrete point interpolation on the two groups of extracted two-dimensional track coordinates to obtain the same number of discrete points and then performing three-dimensional reconstruction; and performing curve fitting on the coordinate points obtained by three-dimensional reconstruction, calculating the retracting track length of the IVUS guide wire, establishing a mapping relation between the guide wire length and the IVUS sequence, and realizing linkage analysis between the contrast images and intravascular ultrasound images. By combining the advantages of CAG and IVUS, the invention accurately realizes the linkage analysis between the two image sequences and the longitudinal section thereof, and improves the diagnosis efficiency of related diseases.
Description
Technical Field
The invention relates to the field of medical image processing and the field of medical equipment, in particular to a CAG and IVUS accurate linkage analysis method and system based on a 3D reconstruction technology.
Background
Cardiovascular related diseases have become a major cause of health hazards and resident death. Along with the aging degree of the population, the prevalence rate of cardiovascular diseases in China also rises year by year. The method for detecting whether coronary artery has atherosclerosis or stenosis and other coronary artery diseases at the initial stage of cardiovascular diseases has great significance for early treatment and intervention control of coronary heart diseases.
At present, the early diagnosis modes of coronary heart disease mainly comprise two modes: coronary Angiography (CAG) and Intravascular Ultrasound (IVUS). Among them, coronary angiography can clearly reveal the anatomical malformation of coronary artery and the position, degree and range of its obstructive lesion, and is the only current diagnostic method capable of directly observing the coronary artery morphology, and is known as "gold standard".
However, in clinical practice, coronary angiography is generally unable to make a correct decision on the lesion at the site of an opening or bifurcation due to the effects of contrast filling and the angle of projection, and there is no way to make a diagnosis of some critical lesions. Under the condition, the intravascular ultrasound IVUS is used for auxiliary examination, the IVUS is not influenced by the irradiation position, the IVUS catheter can be respectively sent to different branch vessels in the imaging process, the shape of a lumen can be observed, the structure or lesion of the vessel wall can be observed, the accumulated degree and range of the lesion can be accurately judged, and unstable plaque, spontaneous dissection, intramural hematoma and the like can be detected. However, although the IVUS can detect the pathological changes of the cross section through the sequence frames after imaging, which is beneficial to making more accurate judgment on the pathological conditions, the spatial position information of the pathological changes cannot be known, so that the interventional therapy after diagnosis still needs coronary angiography for assistance.
In the prior art, there are studies related to the fusion of cardiovascular images (CAG) and intravascular ultrasound Images (IVUS) for the three-dimensional reconstruction of coronary arteries, such as the three-dimensional reconstruction method, apparatus, device and storage medium of coronary arteries disclosed in chinese patent publication No. CN107392994A, including: preprocessing a Coronary Angiography (CAG) image, extracting a blood vessel edge contour and a two-dimensional guide wire, and segmenting an inner membrane and an outer membrane of an intravascular ultrasound Image (IVUS); translating two-dimensional guide wires respectively positioned in CAG images of a first contrast plane and a second contrast plane to the same starting point, constructing a vertical intersecting curved surface, and setting an intersecting line as a three-dimensional guide wire; arranging each frame of IVUS image at equal intervals on a three-dimensional guide wire, and rotating to be vertical to a tangent vector at a corresponding position; rotating the IVUS image on the tangent vector vertical plane, back-projecting the IVUS image on the CAG image, determining the optimal orientation angle according to the back-projection and the distance from the edge contour of the blood vessel to the three-dimensional guide wire, and finally reconstructing the surface of the blood vessel.
But the current related studies have essentially adopted the approach of using the vessel centerline instead of the IVUS guide wire. Due to the influence of the beating of the heart, the blood vessel in the acquired contrast image can also move, and the IVUS guide wire is of a rigid structure, and the track of the IVUS guide wire in the blood vessel is not coincident with the central line of the blood vessel, namely the central line of the blood vessel cannot represent the track of the IVUS guide wire. Therefore, in order to improve the fusion quality of the two images, the retraction trajectory of the ultrasound transducer required for IVUS image imaging needs to be restored as much as possible. The ultrasonic transducer is retracted along the IVUS guide wire, so that the accuracy of fusion of two images can be improved by restoring the track of the IVUS guide wire during the three-dimensional reconstruction operation, and the clinical diagnosis is assisted.
Disclosure of Invention
The invention provides a cardiovascular image (CAG) and intracardiac ultrasound Image (IVUS) accurate linkage analysis method and system based on a 3D reconstruction technology, which can combine the advantages of two different images for diagnosis, quickly and accurately obtain the vascular lesion condition and perform accurate positioning and disease condition evaluation, and the whole operation process can be completed only by a small amount of intervention of an operator.
In order to realize the purpose of the invention, the following technical scheme is adopted:
a CAG and IVUS precise linkage analysis method based on a 3D reconstruction technology comprises the following steps:
1) respectively selecting a single contrast image with a clear IVUS guide wire track from two contrast image sequences under different contrast visual angles, and performing image preprocessing;
2) carrying out interactive segmentation extraction on the IVUS guide wire in the single preprocessed contrast image, and extracting two-dimensional track coordinates of the IVUS guide wire from the two images respectively;
3) performing discrete point interpolation on the two groups of extracted two-dimensional track coordinates to obtain the same number of discrete points and then performing three-dimensional reconstruction;
4) and performing curve fitting on the coordinate points obtained by three-dimensional reconstruction, calculating the retracting track length of the IVUS guide wire, establishing a mapping relation between the guide wire length and the IVUS sequence, and realizing linkage analysis between the contrast images and intravascular ultrasound images.
Preferably, the image preprocessing method in step 1) is as follows: and denoising and enhancing the image based on stochastic resonance.
Preferably, the step of segmenting the IVUS guidewire in the contrast image comprises: selecting a seed point, generating a path and triggering a segmentation end event; in the related operation process of segmenting the guide wire in the contrast image, when the effect of the seed point selection position is poor, the last seed point can be cancelled, a new seed point is generated again, and a new guide wire track is generated by clicking, so that the effect of integrally segmenting the guide wire is ensured.
In the invention, the related operations of segmenting the IVUS guide wire in the contrast image are preferably all completed by an operator operating a mouse, setting a seed point, moving the mouse, generating a path, triggering a segmentation end event and the like. Different events are distinguished by mouse movement, left-click, right-click, double-click, etc. In a further preferred embodiment, the correlation of the IVUS guide wire in the segmentation of the contrast images can also be performed semi-automatically or fully automatically.
Preferably, in the step 2), an intelligent algorithm based on graph theory is adopted to perform interactive segmentation and extraction on the image, a cost function in an intelligent scissor algorithm commonly used in interactive segmentation is improved, and different image features are selected to construct the cost function: regarding the image as a weighted directed graph, wherein each pixel point in the image is a node in the directed graph, and the expression for determining the edge weight is as follows:
l(p,q)＝wCgfC(q)+wSgfS(q)+wGgfG(q)+wGpqgfGpq(p,q)+wHgfH(q)
where p is the pixel in the graph, q is its neighboring pixel, l (p, q) is the edge weight of the edge connecting pixel p and pixel q, wC，wS，wG，wGpqAnd wHAre respectively a weight coefficient, fC(q)，fS(q)，fG(q)，fGpq(p, q) and fH(q) are image feature value cost functions based on different image features, respectively.
In the invention, in order to improve the speed of searching the path with the minimum cost in the image, preferably, the path is generated by adopting Dijkstra routing algorithm according to the seed point.
Preferably, when the three-dimensional reconstruction is performed in the step 3), a damping least square Levenberg-Marquard algorithm is adopted to optimize a system matrix. When the method solves the problem of local convergence of the nonlinear least square problem, a result with global convergence is obtained by using a confidence domain method for reference. In addition, a confidence domain method is adopted to ensure that the optimization result does not fall into local optimization, and the precision of three-dimensional reconstruction is ensured.
Preferably, the linkage analysis is performed to determine the correspondence between the two images by mapping the current IVUS sequence and the distance traveled by the relative point on the contrast image by the back projection, and there are three calculation methods for the calculation distance, as follows:
distance (mm) is withdrawal time x IVUS withdrawal rate
Determining an IVUS sequence frame corresponding to each point on an IVUS guide wire in an angiographic image according to a distance calculation formula, wherein when an observation point of interest moves on the angiographic image, the IVUS sequence frame at the corresponding position also moves; when the IVUS sequence frame changes, the corresponding point on the corresponding contrast image will also change accordingly. That is, in the contrast image, any one of the observation point on the IVUS guide wire, the IVUS sequence frame, and the corresponding position of the IVUS longitudinal section changes, and the other two change correspondingly.
The linkage analysis of the invention is not only the corresponding linkage analysis operation between the cardiovascular radiography image and the cardiovascular ultrasonic image, but also the linkage analysis operation between the cardiovascular ultrasonic image longitudinal section and the cardiovascular ultrasonic image, and the cardiovascular ultrasonic image longitudinal section can be read from the related cardiovascular ultrasonic image imaging instrument to jointly complete the linkage analysis, assist the diagnosis of related diseases and quickly and accurately position the disease position.
The invention also provides a CAG and IVUS precise linkage analysis system based on the 3D reconstruction technology, which comprises the following steps:
the memory is used for storing computer-related executable instructions, computer-related programs and various data required in the linkage analysis process;
and the processor executes the CAG and IVUS precise linkage analysis method according to the steps according to the data in the memory.
When the system is introduced into an intracardiac blood vessel ultrasonic image for linkage analysis, all operations are completed by a mouse, the linkage analysis of a cardiovascular radiography image, an intracardiac blood vessel ultrasonic image sequence and a longitudinal section of the cardiovascular angiography image sequence can be realized, when one object is operated by the mouse, the other two corresponding images can be changed simultaneously, an observation point is positioned, and the information of the three images can be correspondingly displayed.
Compared with the prior art, the invention has the beneficial effects that:
the precise linkage analysis system can effectively combine the advantages of the cardiovascular angiography image and the cardiovascular ultrasound image, and directly restores the motion track of the ultrasound transducer for IVUS image imaging, and uses the improved intelligent scissors algorithm to carry out interactive segmentation to directly extract the IVUS guide wire track in the angiography image instead of using the center line of the blood vessel or generating the curve in the blood vessel to replace the IVUS guide wire track, so that the improved intelligent scissors algorithm has higher segmentation speed, and the curve edge is smoother and has less saw teeth. When the target function in the three-dimensional reconstruction is solved, a trust domain method is adopted, parameters are continuously updated according to the ratio of the actual descent amount to the predicted descent amount in the iteration process, so that the parameters have global convergence, a three-dimensional IVUS guide wire is further reconstructed, and finally, the linkage analysis among the cardiovascular angiography image, the cardiovascular ultrasound image sequence and the longitudinal section thereof can be accurately realized according to the mapping relation between the length of the guide wire and the IVUS sequence, the interaction is convenient and fast, and the diagnosis efficiency of related diseases is greatly improved.
Drawings
Fig. 1 is a schematic diagram illustrating a cardiovascular image (CAG) and an intracardiac ultrasound Image (IVUS) precise linkage analysis principle based on a 3D reconstruction technique according to an embodiment of the present invention;
FIG. 2 is a flow chart of a technical route for linkage analysis in an embodiment of the present invention;
FIG. 3 is a schematic illustration of a segmentation operation for manipulating a contrast image in accordance with an embodiment of the present invention;
fig. 4 is a schematic diagram of a three-dimensional reconstruction module according to an embodiment of the present invention.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and thus the present invention is not limited to the specific embodiments disclosed below.
Referring to fig. 1 to 4, the specific implementation steps of the CAG and IVUS precise linkage analysis method based on the 3D reconstruction technology in this embodiment are as follows:
1) a sequence of cardiovascular images generated by a single-plane imaging system under two different imaging perspectives is introduced, and a single image in which the IVUS guidewire trajectory is clear is selected, as shown in fig. 2.
2) The preprocessing operation of the image is performed, the random resonance denoising enhancement operation and the like are performed on the contrast image, the noise in the image is reduced, and the interested part of the image is easier to segment, as shown in fig. 2.
3) The mouse is operated to perform interactive extraction on the IVUS guide wire track in the image, and two-dimensional track coordinates of the IVUS guide wire are respectively extracted, as shown in FIG. 2. Along the edge part of the guide wire track in the contrast image, a left mouse button clicks a seed point, the seed point is displayed on a blue point on the image, then the mouse is moved, the moving path of the mouse is automatically attached to the IVUS guide wire track, a green line is generated until the segmentation operation of the whole guide wire track is completed, and the method is shown in figure 3.
4) For the extracted coordinate points of the two groups of IVUS guide wire tracks, discrete point interpolation operation is respectively carried out, and the discrete points are interpolated into the same number of discrete points, as shown in FIG. 2.
5) And performing three-dimensional reconstruction of the coordinate points based on the two groups of two-dimensional coordinate points obtained in the operation step 4). The three-dimensional reconstruction method adopts two-dimensional coordinate points as elements of three-dimensional matching and three-dimensional reconstruction, and matching and reconstruction are required to be carried out point by point. Meanwhile, parameter optimization operation of a geometric transformation matrix of the system is required.
6) And (3) performing curve fitting operation on the three-dimensional coordinate points obtained in the operation step 5), and fitting and calculating the length of the whole IVUS guide wire withdrawing route by using a B-spline fitting method in computer graphics, as shown in figure 2.
7) And (3) importing a corresponding IVUS image sequence according to the length of the retraction path obtained in the operation step 6), and realizing linkage analysis among the contrast image (CAG), the intravascular ultrasound Image (IVUS) sequence and the intravascular ultrasound Image (IVUS) longitudinal section based on the corresponding relation between the total length of the retraction path and the IVUS sequence. After the desired effect is achieved, the system is exited.
In this embodiment, an intelligent algorithm based on graph theory is used in the process of performing interactive segmentation operation by operating a mouse, the algorithm improves a cost function in an original intelligent scissor algorithm, the new cost function is constructed by a series of new image characteristic value functions, the cost value difference between an edge part and a non-edge part is enlarged to the maximum extent, a weight is set for an edge formed by each pixel point and adjacent pixel points on an image by regarding the image as a weighted directed graph, and the expression is as follows:
l(p,q)＝wCgfC(q)+wSgfS(q)+wGgfG(q)+wGpqgfGpq(p,q)+wHgfH(q)
where p is the pixel in the graph, q is its neighboring pixel, l (p, q) is the edge weight of the edge connecting pixel p and pixel q, wC，wS，wG，wGpqAnd wHAre respectively a weight coefficient, fC(q)，fS(q)，fG(q)，fGpq(p, q) and fH(q) the cost function of the image characteristic value of the pixel point q based on the Canny operator, the cost function of the image characteristic value of the pixel point q based on the Scharr operator, the gradient amplitude value of the pixel point q, the gradient transformation adjustment function of the pixel point p and the pixel point q, and the histogram adjustment function of the pixel point q are respectively.
As shown in fig. 3, the entire weighted directed graph can be determined by calculating the weighted values of each pixel point on the image and the surrounding pixel points. Each seed point set by the user through mouse operation is a point in the weighted directed graph, and the shortest path between the seed points set by the user can be obtained by utilizing the algorithm of the shortest path. As long as the seed points are reasonably set, the shortest path obtained is a path with the minimum cost, namely a withdrawal trajectory path of the IVUS guide wire to be segmented.
In addition, in order to accelerate the speed of shortest path calculation, a fast Dijkstra path finding algorithm is adopted in the embodiment, so that a path meeting the minimum cost can be quickly found out when the mouse moves, and the path is used as a retracing track path of the IVUS guide wire.
In this embodiment, in order to obtain images at the same cardiac time, an ECG cardiac gating method is used to acquire data.
In this embodiment, in order to perform three-dimensional reconstruction, it is necessary to acquire imaging parameters of the contrast device, including a distance from the emission source to the image intensifier, a distance from the emission source to the target, a field of view, a radiation magnification, a pixel width, a left-right angle, a front-back angle, and the like.
In this embodiment, in order to ensure the correspondence between points at two viewing angles in the three-dimensional reconstruction, two groups of discrete coordinate points obtained by interactive extraction at two different viewing angles are combined into the same number of discrete points by a B-spline interpolation method, and then an objective function to be optimized is obtained according to the rotation matrix, and the objective function is solved.
The target function belongs to a nonlinear least square problem, the damping least square Levenberg-Marquardt method is adopted to carry out optimization solution on the target function in the embodiment, the problems of local convergence and the like which may occur in the target function are solved through a confidence domain method, and parameters are continuously updated according to the ratio of the actual descent quantity to the predicted descent quantity in the iteration process, so that the target function has global convergence, cannot fall into local optimization, and is more stable in result, which is the key for ensuring the three-dimensional reconstruction precision.
In this embodiment, all kinds of parameters and information required in all steps can be acquired from Tag information in a DICOM sequence corresponding to a cardiovascular angiography image (CAG) and an intravascular ultrasound Image (IVUS).
In another embodiment, an accurate linkage analysis system of a cardiovascular angiography image (CAG) and an intracardiac ultrasound Image (IVUS) based on a 3D reconstruction technique includes:
the memory is used for storing computer-related executable instructions, computer-related programs and various data required in the linkage analysis process;
the processor can be used together with the memory, can run a system program, execute a related operation instruction, and complete the CAG and IVUS precise linkage analysis method according to steps;
the input and output devices meet the interaction requirements of users and comprise a mouse, a display or other touch input devices and the like.
The above description is only exemplary of the preferred embodiments of the present invention, and is not intended to limit the present invention, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A CAG and IVUS precise linkage analysis method based on a 3D reconstruction technology is characterized by comprising the following steps:
1) respectively selecting a single contrast image with a clear IVUS guide wire track from two contrast image sequences under different contrast visual angles, and performing image preprocessing;
2) carrying out interactive segmentation extraction on the IVUS guide wire in the single preprocessed contrast image, and extracting two-dimensional track coordinates of the IVUS guide wire from the two images respectively;
3) performing discrete point interpolation on the two groups of extracted two-dimensional track coordinates to obtain the same number of discrete points and then performing three-dimensional reconstruction;
4) and performing curve fitting on the coordinate points obtained by three-dimensional reconstruction, calculating the retracting track length of the IVUS guide wire, establishing a mapping relation between the guide wire length and the IVUS sequence, and realizing linkage analysis between the contrast images and intravascular ultrasound images.
2. The CAG and IVUS precise linkage analysis method based on the 3D reconstruction technology according to claim 1, characterized in that the image preprocessing method of the step 1) is as follows: and denoising and enhancing the image based on stochastic resonance.
3. The CAG and IVUS precise linkage analysis method based on the 3D reconstruction technology as claimed in claim 1, wherein the step of segmenting the IVUS guide wire in the contrast image comprises: selecting a seed point, generating a path and triggering a segmentation end event;
when the effect of the seed point selection position is not good, the last seed point can be cancelled, and a new seed point is regenerated.
4. The CAG and IVUS precise linkage analysis method based on the 3D reconstruction technology as claimed in claim 3, wherein in the step 2), an intelligent scissors algorithm is adopted to perform interactive segmentation extraction on the image: regarding the image as a weighted directed graph, wherein each pixel point in the image is a node in the directed graph, and the expression for determining the edge weight is as follows:
l(p,q)＝wCgfC(q)+wSgfS(q)+wGgfG(q)+wGpqgfGpq(p,q)+wHgfH(q)
where p is the pixel in the graph, q is its neighboring pixel, l (p, q) is the edge weight of the edge connecting pixel p and pixel q, wC，wS，wG，wGpqAnd wHAre respectively a weight coefficient, fC(q)，fS(q)，fG(q)，fGpq(p, q) and fH(q) are image feature value cost functions based on different image features, respectively.
5. The CAG and IVUS precise linkage analysis method based on the 3D reconstruction technology as claimed in claim 3, characterized in that according to the seed points, a Dijkstra path-finding algorithm is adopted to generate the path.
6. The CAG and IVUS precise linkage analysis method based on the 3D reconstruction technology as claimed in claim 1, wherein in the step 3) of three-dimensional reconstruction, a damping least square Levenberg-Marquard algorithm is adopted to optimize the system matrix.
7. The CAG and IVUS precise linkage analysis method based on 3D reconstruction technology as claimed in claim 1, wherein the linkage analysis is performed to determine the corresponding relationship between the two images by mapping the current sequence of IVUS and the distance traveled by the relative point on the contrast image by back projection, and there are three calculation methods for the calculation distance, as follows:
distance (mm) is withdrawal time x IVUS withdrawal rate
Determining an IVUS sequence frame corresponding to each point on an IVUS guide wire in an angiographic image according to a distance calculation formula, wherein when an observation point of interest moves on the angiographic image, the IVUS sequence frame at the corresponding position and a longitudinal section where the IVUS sequence frame is located also move; when the IVUS sequence frame changes, the corresponding point on the corresponding contrast image will also change accordingly.
8. The CAG and IVUS precision linkage analysis system based on 3D reconstruction technology according to claim 1, characterized by comprising:
the memory is used for storing computer-related executable instructions, computer-related programs and various data required in the linkage analysis process;
a processor for performing a CAG and IVUS precision linked analysis method as claimed in any one of claims 1 to 7 based on data in said memory.
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| CN114145719A (en) * | 2022-02-08 | 2022-03-08 | 天津恒宇医疗科技有限公司 | Method and system for three-dimensional fusion of dual-mode coronary vessel images |
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