Atherosclerotic plaque segmentation at human carotid artery based on multiple contrast weighting MR images

The aims of this study are (1) to propose an image segmentation framework for Multiple Contrast Weighting MR images; and (2) to analyze the agreement between segmentation results and histology sections. The proposed technique is actually based on the mean-shift density estimation algorithm and carefully designed to overcome the drawbacks in other existing methods. First, it has a very reliable and accurate initialization scheme that guarantees all potential clusters are within estimation. Secondly, the proposed method introduces a dynamic sphere mechanism that makes the mean-shift vector more reliable even with poor initialization. It can also enhance the accuracy of cluster center estimation when the searching processing is approaching the mode. Experimental results and comparison with histology sections demonstrate its encouraging performance. Moreover the proposed approach can be easily extended to other general-purpose low-level image analysis problems.