It is very important for physicians to accurately determine breast tumor location, size and shape in ultrasound image. The
precision of breast tumor volume quantification relies on the accurate segmentation of the images. Given the known
location and orientation of the ultrasound probe, We propose using freehand three dimensional (3D) ultrasound to
acquire original images of the breast tumor and the surrounding tissues in real-time, after preprocessing with anisotropic
diffusion filtering, the segmentation operation is performed slice by slice based on the level set method in the image
stack. For the segmentation on each slice, the user can adjust the parameters to fit the requirement in the specified image
in order to get the satisfied result. By the quantification procedure, the user can know the tumor size varying in different
images in the stack. Surface rendering and interpolation are used to reconstruct the 3D breast tumor image. And the
breast volume is constructed by the segmented contours in the stack of images. After the segmentation, the volume of the
breast tumor in the 3D image data can be obtained.
In this paper, we propose a new model based on C-V model, this model based on intra-region similar and inter-region
dissimilar properties, adjusting the parameters automatically using the region mean values inside and outside the curve,
is suitable for weak edge image segmentation. In the segmentation of the 3-D ultrasonic breast tumor, the segmentation
speed of this model is faster than the C-V model, and the segmentation result is gratifying.