Segmenting images by combining selected atlases on manifold

Yihui Cao, Yuan Yuan, Xuelong Li, Baris Turkbey, Peter L. Choyke, Pingkun Yan

科研成果: 书/报告/会议事项章节会议稿件同行评审

35 引用 (Scopus)

摘要

Atlas selection and combination are two critical factors affecting the performance of atlas-based segmentation methods. In the existing works, those tasks are completed in the original image space. However, the intrinsic similarity between the images may not be accurately reflected by the Euclidean distance in this high-dimensional space. Thus, the selected atlases may be away from the input image and the generated template by combining those atlases for segmentation can be misleading. In this paper, we propose to select and combine atlases by projecting the images onto a low-dimensional manifold. With this approach, atlases can be selected according to their intrinsic similarity to the patient image. A novel method is also proposed to compute the weights for more efficiently combining the selected atlases to achieve better segmentation performance. The experimental results demonstrated that our proposed method is robust and accurate, especially when the number of training samples becomes large.

源语言英语
主期刊名Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings
272-279
页数8
版本PART 3
DOI
出版状态已出版 - 2011
已对外发布
活动14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011 - Toronto, ON, 加拿大
期限: 18 9月 201122 9月 2011

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
编号PART 3
6893 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011
国家/地区加拿大
Toronto, ON
时期18/09/1122/09/11

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