首页 | 本学科首页   官方微博 | 高级检索  
     


A multiresolution diffused expectation-maximization algorithm for medical image segmentation
Authors:Boccignone Giuseppe  Napoletano Paolo  Caggiano Vittorio  Ferraro Mario
Affiliation:Natural Computation Lab, DIIIE-Universitá di Salerno, via Ponte Don Melillo, 1, 84084 Fisciano (SA), Italy. boccig@unisa.it
Abstract:
In this paper a new method for segmenting medical images is presented, the multiresolution diffused expectation-maximization (MDEM) algorithm. The algorithm operates within a multiscale framework, thus taking advantage of the fact that objects/regions to be segmented usually reside at different scales. At each scale segmentation is carried out via the expectation-maximization algorithm, coupled with anisotropic diffusion on classes, in order to account for the spatial dependencies among pixels. This new approach is validated via experiments on a variety of medical images and its performance is compared with more standard methods.
Keywords:Image segmentation   Expectation-maximization   Multiresolution
本文献已被 ScienceDirect PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号