A novel level set model with automated initialization and controlling parameters for medical image segmentation

In this paper, a level set model without the need of generating initial contour and setting controlling parameters manually is proposed for medical image segmentation. The contribution of this paper is mainly manifested in three points. First, we propose a novel adaptive mean shift clustering method based on global image information to guide the evolution of level set. By simple threshold processing, the results of mean shift clustering can automatically and speedily generate an initial contour of level set evolution.

Source: Computerized Medical Imaging and Graphics - December 19, 2015 Category: Radiology Authors: Qingyi Liu, Mingyan Jiang, Peirui Bai, Guang Yang Source Type: research