A Novel Integration Scheme Based on Mean Shift and Region-Scalable Fitting Level Set for Medical Image Segmentation

摘要

In this study, a novel integration scheme for coupling the results of mean shift with initial contours of the region-scalable fitting level set method (RSF model) is presented. There are two main contributions in the study. First, a new adaptive threshold formula to fit dynamic range of the mean shift clustering results is proposed. Second, a double-side mapping mode is presented to improve the robustness of initialization. Experimental results demonstrate the adaptability and robustness of the proposed method, and accurate segmentation could be obtained for medical images.