A Method of Obtaining Initial Contour in Ultrasound Image Segmentation Based on Active Contour Model
An active contour model and ultrasonic image technology, applied in image analysis, image data processing, instruments, etc., can solve the problems of inaccuracy, time-consuming and laborious, etc., and achieve the effect of improving efficiency and accuracy, and clear and accurate initial contour
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Embodiment 1
[0029] After training 60 existing liver tumor ultrasound images, the standard feature vector A of liver tumor ultrasound images is obtained 0 . That is, first calculate the 24 texture eigenvalues of each image using the gray level co-occurrence matrix, then 60 groups of eigenvectors containing 24 elements will be obtained, and all eigenvectors will be processed by mathematical linear regression method to obtain a standard The feature vector is to find a vector A with the shortest average distance to the group of feature vectors. The corresponding texture feature values in the vector A are the standard values we need to obtain. Then add the feature vector A to the standard ellipse fitting data 0.7 and the prior size of the liver tumor calculated by the long and short axis of the tumor area marked by the doctor during the ultrasound detection process in the ultrasound image to be tested, and then we get a 26-element standard eigenvector A 0 .
[0030] figure 2 (A) is the ul...
Embodiment 2
[0032] After training 60 ultrasound images of uterine fibroids, the standard feature vector A of uterine fibroids ultrasound images is obtained 0 . That is, first calculate the 24 texture eigenvalues of each image using the gray level co-occurrence matrix, then 60 groups of eigenvectors containing 24 elements will be obtained, and all eigenvectors will be processed by mathematical linear regression method to obtain a standard The feature vector is to find a vector A with the shortest average distance to the group of feature vectors. The corresponding texture feature values in the vector A are the standard values we need to obtain. Then add the feature vector A to the standard ellipse fitting data 0.7 and the prior size of the uterine fibroids calculated from the long and short axis of the tumor area marked by the doctor during the ultrasound detection process in the ultrasound image to be tested, then you get A standard eigenvector A with 26 elements 0 .
[0033] image 3 ...
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