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Multi-threshold ultrasonic image segmentation method based on differential search algorithm

A technology of ultrasonic image and search algorithm, applied in the field of image processing, can solve the problems of inaccurate segmentation, affecting the accuracy of segmentation, and inability to segment ultrasonic images more completely, and achieve accurate segmentation, good segmentation effect, and fast segmentation speed

Active Publication Date: 2020-04-24
KUNMING UNIV OF SCI & TECH
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Problems solved by technology

It also solves the problem that the ultrasonic image cannot be completely segmented when the segmented area is close to the ideal area, especially when the ultrasonic image contains multiple targets in both black and white target areas
[0006] The technical solution of the present invention is: a multi-threshold ultrasonic image segmentation method based on a differential search algorithm, firstly, the ultrasonic image is preprocessed, and the ultrasonic image is denoised by using a bilateral filter, which is used to solve the problem of noise in the ultrasonic image. The problem of accuracy; then the threshold value of ultrasonic image segmentation is obtained by the Otsu-DS algorithm, which is used to solve the problem of inaccurate segmentation, and at the same time can achieve fast segmentation, wherein the segmentation threshold value of ultrasonic image is the value when the variance function between classes is maximized; Finally, the ultrasonic image is segmented by using the multiple thresholds obtained, and the segmentation result is obtained

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  • Multi-threshold ultrasonic image segmentation method based on differential search algorithm
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  • Multi-threshold ultrasonic image segmentation method based on differential search algorithm

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Embodiment 1

[0029] Embodiment 1: as figure 1 , figure 2 As shown, a multi-threshold ultrasonic image segmentation method based on differential search algorithm, for images such as figure 2(a) Preprocessing, first use bilateral filter to denoise, to solve the problem that the existence of image noise affects the accuracy of segmentation; then use the Otsu-DS algorithm to obtain the threshold of ultrasonic image segmentation; finally use the obtained multiple thresholds Segment the ultrasound image to obtain the segmentation result. In the experiment of this example, the region growing method uses 4 neighborhoods, and the similarity distance between gray values ​​between pixels is set to be less than 0.05, and the growth segmentation is performed after selecting the seed point of the target area. The active contour adopts the active contour of the CV model, and at the same time sets the initial contour around the target area, and sets the number of iterations to 500 for the evolution of...

Embodiment 2

[0044] Embodiment 2: as figure 1 , image 3 As shown, a multi-threshold ultrasonic image segmentation method based on differential search algorithm, this embodiment is the same as embodiment 1, the difference is:

[0045] For images such as image 3 (a) For processing, firstly use a bilateral filter for denoising to solve the problem that the existence of image noise affects the accuracy of segmentation; then use the Otsu-DS algorithm to obtain the threshold for ultrasonic image segmentation; finally use the obtained multiple thresholds for segmentation Ultrasound images to obtain segmentation results. In the experiment of this example, the region growing method uses 4 neighborhoods, and the similarity distance between gray values ​​between pixels is set to be less than 0.05, and the growth segmentation is performed after selecting the seed point of the target area. The active contour adopts the active contour of the CV model, and at the same time sets the initial contour a...

Embodiment 3

[0059] Embodiment 3: as figure 1 , Figure 4As shown, a multi-threshold ultrasonic image segmentation method based on differential search algorithm, for images such as Figure 4 (a) Preprocessing, first use bilateral filter to denoise, to solve the problem that the existence of image noise affects the accuracy of segmentation; then use the Otsu-DS algorithm to obtain the threshold of ultrasonic image segmentation; finally use the obtained multiple thresholds Segment the ultrasound image to obtain the segmentation result. In the experiment of this example, the region growing method uses 4 neighborhoods, and the similarity distance between gray values ​​between pixels is set to be less than 0.05, and the growth segmentation is performed after selecting the seed point of the target area. The active contour adopts the active contour of the CV model, and at the same time sets the initial contour around the target area, and sets the number of iterations to 500 for the evolution of...

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Abstract

The invention relates to a multi-threshold ultrasonic image segmentation method based on a differential search algorithm, and belongs to the technical field of image processing. The method comprises the following steps: firstly, preprocessing an ultrasonic image, and denoising the ultrasonic image by using a bilateral filter to solve the problem that noise in the ultrasonic image affects segmentation accuracy; secondly, obtaining an ultrasonic image segmentation threshold value through an Otsu-DS algorithm and solving the problem of inaccurate segmentation, and performing rapid segmentation, wherein the ultrasonic image segmentation threshold value is a value obtained when an inter-class variance function is maximum; and finally, segmenting the ultrasonic image by using the plurality of obtained thresholds to obtain a segmentation result. According to the method of the invention, the ultrasonic image can be effectively segmented, the segmentation efficiency is relatively high, and a relatively good effect can be achieved.

Description

technical field [0001] The invention relates to a multi-threshold ultrasonic image segmentation method based on a differential search algorithm, which belongs to the technical field of image processing. Background technique [0002] As a kind of medical imaging, ultrasound image plays an important role in medical clinical diagnosis. With the development of imaging medicine, ultrasound image segmentation is becoming more and more important in medical clinical diagnosis. Ultrasound image segmentation is an important part of the computer-aided diagnosis (CAD) system. condition. [0003] In the current research, the ultrasonic image segmentation methods used can be roughly divided into: threshold method, clustering method, and active contour. Thresholding method is a common image segmentation method, which is often used in the segmentation of medical images, including CT, MRI and ultrasound images. Among them, there is relatively large speckle noise in the ultrasound image, ...

Claims

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Application Information

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IPC IPC(8): G06T7/136G06T5/00
CPCG06T7/136G06T2207/10132G06T2207/20028G06T5/70
Inventor 邵党国朱小方
Owner KUNMING UNIV OF SCI & TECH
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