Multi-atlas based image selection with label image constraint

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	Multi-atlas based image selection with label image constraint
	Yihui Cao; Xuelong Li; Pingkun Yan
	2012
会议名称	11th IEEE International Conference on Machine Learning and Applications, ICMLA 2012
会议录名称	Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012
卷号	1
页码	311-316
会议日期	December 12, 2012 - December 15, 2012
会议地点	Boca Raton, FL, United states
出版地	2001 L Street N.W., Suite 700, Washington, DC 20036-4928, United States
出版者	IEEE Computer Society
产权排序	1
摘要	Atlas selection plays an important role in multiatlas based image segmentation. In atlas selection methods, manifold learning based techniques have recently emerged as very promisingly. However, due to the complexity of anatomical structures in raw images, it is difficult to get accurate atlas selection results by measuring only the distance between raw images on the manifolds. In this paper, we tackle this problem by proposing a label image constrained atlas selection (LICAS) method to exploit the shape and size information of the regions to be segmented from the label images. Constrained by the label images, a new manifold projection method is developed to help uncover the intrinsic similarity between the regions of interest across images. Compared with other existing methods, the experimental results of segmentation on 60 Magnetic Resonance (MR) images showed that the selected atlases are closer to the target structure and more accurate segmentation can be obtained by using the proposed method.
作者部门	光学影像分析与学习中心
收录类别	EI
ISBN号	9780769549132
语种	英语
文献类型	会议论文
条目标识符	http://ir.opt.ac.cn/handle/181661/20914
专题	光谱成像技术研究室
推荐引用方式 GB/T 7714	Yihui Cao,Xuelong Li,Pingkun Yan. Multi-atlas based image selection with label image constraint[C]. 2001 L Street N.W., Suite 700, Washington, DC 20036-4928, United States:IEEE Computer Society,2012:311-316.

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