Method for acquiring initial contour in ultrasonic image segmentation based on active contour model

An active contour model, ultrasound image technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as inaccuracy, time-consuming and laborious, and achieve the effect of improving efficiency and accuracy, and the initial contour is clear and accurate

Inactive Publication Date: 2014-07-09
WUHAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] However, the model requires an initial contour. If the initial contour is obtained manually and then converged, it is time-consuming and laborious, and it is not accurate enough.

Method used

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  • Method for acquiring initial contour in ultrasonic image segmentation based on active contour model
  • Method for acquiring initial contour in ultrasonic image segmentation based on active contour model
  • Method for acquiring initial contour in ultrasonic image segmentation based on active contour model

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Embodiment 1

[0029] The standard feature vector A of liver tumor ultrasound images is obtained by training 60 existing ultrasound images of liver tumors 0 . That is to say, for each image, its 24 texture eigenvalues ​​are calculated by using the gray level co-occurrence matrix, then 60 sets of eigenvectors containing 24 elements will be obtained, and all the eigenvectors will be processed by mathematical linear regression to obtain a standard The eigenvector, that is, by finding a vector A with the shortest average distance to the group of eigenvectors, the corresponding texture eigenvalues ​​in the vector A are the standard values ​​we need to obtain. Then add the standard ellipse fitting data of 0.7 to the feature vector A and the prior size of the liver tumor calculated from the long and short axes of the tumor area marked by the doctor during the ultrasonic detection process in the ultrasonic image to be tested, then we get an element containing Standard eigenvector A of 26 elements ...

Embodiment 2

[0032] After training on 60 existing ultrasound images of uterine fibroids, the standard feature vector A of ultrasound images of uterine fibroids is obtained 0 . That is to say, for each image, its 24 texture eigenvalues ​​are calculated by using the gray level co-occurrence matrix, then 60 sets of eigenvectors containing 24 elements will be obtained, and all the eigenvectors will be processed by mathematical linear regression to obtain a standard The eigenvector, that is, by finding a vector A with the shortest average distance to the group of eigenvectors, the corresponding texture eigenvalues ​​in the vector A are the standard values ​​we need to obtain. Then add the standard ellipse fitting data of 0.7 to the feature vector A and the prior size of uterine fibroids calculated by the long and short axis of the tumor area marked by the doctor during the ultrasonic detection process in the ultrasonic image to be tested, then we get A standard eigenvector A with 26 elements ...

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Abstract

The invention discloses a method for acquiring an initial contour in ultrasonic image segmentation based on an active contour model. The method comprises the following steps that the textural features of an ultrasonic image tumor area are trained, and a normal vector is formed by the textural features, a standard elliptical experience value and the tumor prior size in an ultrasonic image to be detected; the ultrasonic image to be detected is preprocessed; dynamic threshold segmentation is carried out on the image; all closed contours generated in the dynamic threshold segmentation result are extracted to form corresponding sub-images; 24 textural features of the sub-images, an ellipse fitting result parameter and the number of pixels in the closed contours of the sub-images are calculated, and a vector is formed by 26 data; the distance between the obtained vector and the normal vector obtained from the tumor area through training is calculated, and the closed contour, corresponding to the vector with the smallest distance, in the sub-images is the contour of a tumor in the segmented ultrasonic image. The method solves the problem that the ultrasonic image has much noise and is fuzzy in boundary, and the initial contour accuracy is high.

Description

technical field [0001] The invention relates to a method for obtaining initial contours in ultrasonic image segmentation based on active contours, and belongs to the field of ultrasonic image processing. Background technique [0002] With the emergence of high-intensity focused ultrasound, non-invasive treatment of tumors has become more and more widely used. This treatment system has great advantages in clinical practice, such as no surgery, no scars, non-invasive or minimal trauma, real-time detection and treatment , not limited by the size of the tumor, and the total cost is low. These advantages all determine that the high-intensity focused ultrasound therapy system has great development and application prospects. The most important thing in the high-intensity focused ultrasound therapy system is to navigate the patient's tumor in real time. The navigation process requires localization of tumors in real-time ultrasound images. Changing the traditional manual positioni...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 张东龙群芳刘雨周静杨艳
Owner WUHAN UNIV
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