Brain image segmentation based on multiple atlas active contour model

作者：Zhang, Ming Hui; Lu, Zhen Tai^*; Zhang, Juan; Yang, Wei; Chen, Wu Fan; Zhang, Yu

来源：Chinese Journal of Computers, 2016, 39(7): 1490-1500.

DOI：10.11897/SP.J.1016.2016.01490

• Active contour model
• Atlas prior
• Atlas registration
• Local information
• Local similarity measure
• Prior information
• Registration error
• Segmentation performance

Various brain diseases are closely related with the position, size and shape changes of key brain structures, such as hippocampus, accumbens, caudatum, and thalamus. It requires the accurate segmentation of these key brain structures to measure their changes. However, the traditional segmentation is not accurate enough because these structures have no clear contrasted boundaries in MR images. In this paper, we propose a novel segmentation framework that combined the multi-atlas registration and active contour model. We utilize the prior information of atlases and the gray information of target image. The shape prior information be incorporated into the active contour model modeling to improve the segmentation performance. the active contour model will correct the label errors in the label fusion procedure. The framework consists of three terms. First one is the atlas prior term, which uses the local similarity measure as weight to incorporate the atlas information. The second one is data term, which uses the local information of target image to correct the registration errors. The third one is smooth term, which was used to ensure the smoothness of the evolution curve. Experiments results demonstrate the efficacy and accuracy of the proposed method.

• 出版日期2016
• 单位南方医科大学