Coupled dictionary learning for joint MR image restoration and segmentation | |
Xuesong, Yang1,2; Yong, Fan3 | |
2018-03-02 | |
会议名称 | SPIE medical imaging |
会议日期 | 2018-3-2 |
会议地点 | Houston, Texas, United States |
摘要 | To achieve better segmentation of MR images, image restoration is typically used as a preprocessing step, especially for low-quality MR images. Recent studies have demonstrated that dictionary learning methods could achieve promising performance for both image restoration and image segmentation. These methods typically learn paired dictionaries of image patches from different sources and use a common sparse representation to characterize paired image patches, such as low-quality image patches and their corresponding high quality counterparts for the image restoration, and image patches and their corresponding segmentation labels for the image segmentation. Since learning these dictionaries jointly in a unified framework may improve the image restoration and segmentation simultaneously, we propose a coupled ictionary learning method to concurrently learn dictionaries for joint image restoration and image segmentation based on sparse representations in a multi-atlas image segmentation framework. Particularly, three dictionaries, including a |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/23580 |
专题 | 脑图谱与类脑智能实验室_脑网络组研究 |
通讯作者 | Xuesong, Yang |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academic of Sciences, Beijing 100190, China 2.University of Chinese Academic of Sciences, Beijing 100190, China 3.Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Xuesong, Yang,Yong, Fan. Coupled dictionary learning for joint MR image restoration and segmentation[C],2018. |
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