Knowledge Commons of Institute of Automation,CAS
Feature extraction using convolutional neural networks for multi-atlas based image segmentation | |
Xuesong, Yang1,2![]() | |
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 | Multi-atlas based image segmentation in conjunction with pattern recognition based label fusion strategies has achieved promising performance in a variety of image segmentation problems, including hippocampus segmentation from MR images. The pattern recognition based label fusion consists of image feature extraction and pattern recognition components. Since the feature extraction component plays an important role in the pattern recognition based label fusion, a variety of feature extraction methods have been proposed to extract image features, including texture features and random projection features. However, these feature extraction methods are not adaptive to different segmentation problems. Following the success of convolutional neural networks in image feature extraction, we propose a feature extraction method based on convolutional neural networks for multi-atlas based image segmentation. The proposed |
收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/23579 |
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. Feature extraction using convolutional neural networks for multi-atlas based image segmentation[C],2018. |
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1057439.pdf(813KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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