[Segmentation of breast tumor ultrasound images based on an improved C-V model].
This paper proposes an improved C-V model, which can avoid the step of re-initialization and simplify the formation of the initial level set function, thus the speed of segmentation can be accelerated greatly. 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 for the refined segmentation algorithm. This flow has improved not only the accuracy, but also the efficiency of the segmentation algorithm. The experiments show that the proposed algorithm could extract the contour of the breast tumor from the ultrasound images efficiently and accurately, which is fundamentally important for the following target feature extraction and analysis.
Ha
Zhang
Z
Department of Electronic Engineering and Information Science, USTC, Hefei. hazhang@mail.ustc.edu.en
Li
Chuan-fu
CF
Wang
Jin-ping
JP
Zhou
Kang-yuan
KY
He
Li
L
D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016217:Ultrasonography, Mammary / Q000379:methods*