Furthermore, based on the grayscale distribution characteristics of the breast tumor ultrasound images and on the hypothesis of piecewise constant in the C-V model, a semiautomatic segmentation flow has been presented, in which the rough contour is sketched first, and then a subimage would be obtained.

The number of unnecessary biopsies of breast lesions may be further reduced with the use of effective computer-aided diagnosis (CAD) system that would improve the specificity of discriminating malignant from benign lesions on breast ultrasound images.

Objective To promote stability and accuracy of gradient vector flow (GVF) deformable models by improving external potential force field of ultrasound images under speckle noisy environments.

Objective To improve the flexibility and stability of the filter in speckle reduction of ultrasound images.

This article presents an algorithm for semiautomatic segmentation of ultrasound images combining user intervention into the B spline snake models using a new kind of force field and a new control point insertion strategy.

Breast tumor classification based on shape features of ultrasonic images;

Quantitative analysis of fatty liver ultrasonic images;

Discussion on extraction of planar contour from ultrasonic image and rebuilding process of three-dimensional image;

Automatic detection of breast tumor regions in medical ultrasound images with texture features;

Multi-characteristics recognition of breast tumor ultrasound images combining with elasticity parameters;

The classification of the uterine myoma and the uterine adenomyosis from ultrasound images mainly depends on doctors experience and lacks objective criterions by now.