Active contour model driven by global and local intensity information for ultrasound image segmentation. (15th June 2018) - Fang, Lingling; Qiu, Tianshuang; Liu, Yin; Chen, Chaofeng
Abstract: Due to the abundant noise, blurry boundaries, and intensity inhomogeneities present in ultrasound (US) images, it is a difficult task to segment US images accurately. In this paper, we propose a novel active contour method that combines global and local region information to achieve this task. The global information can segment US images with noise and blurry boundaries; while the local information can settle the intensity homogeneities of images. The proposed method can be directly applied to synthetic, real, and US-images segmentation. Results demonstrate the superiority of the proposed method over other representative algorithms. Moreover, we also extend the proposed method to vector-valued images. Experiments are performed to testify the feasibility of the method, and the proposed vector-valued idea can be applied to the medical co-segmentation in the future.