Knowledge Commons of Institute of Automation,CAS
An unsupervised network for fast microscopic image registration | |
Shu, Chang1,2; Chen, Xi2; Xie, Qiwei2; Han, Hua2,3,4 | |
2018 | |
会议名称 | SPIE Medical Imaging, 2018 |
会议录名称 | Medical Imaging 2018: Digital Pathology |
卷号 | 10581 |
页码 | 105811D |
会议日期 | 10-15 FEBRUARY, 2018 |
会议地点 | Houston, Texas, United States |
摘要 | At present, deep learning is widely used and has achieved excellent results in many fields except in the field of image registration, the reasons are two-fold: Firstly all the steps of deep learning should be derivable; nevertheless, the nonlinear deformation which is usually used in registration algorithms is hard to be depicted by explicit function. Secondly, success of deep learning is based on a large amount of labeled data, this is problematic for the application in real scenes. To address these concerns, we propose an unsupervised network for image registration. In order to integrate registration process into deep learning, image deformation is achieved by resampling, which can make deformation step derivable. The network optimizes its parameters directly by minimizing the loss between registered image and reference image without ground truth. To further improve algorithm's accuracy and speed, we incorporate coarse-to-fine multi-scale iterative scheme. We apply our method to register microscopic section images of neuron tissue. Compared with highly fine-tuning method sift flow, our method achieves similar accuracy with much less time. |
关键词 | Microscopic image registration deep learning unsupervised learning coarse-to-fine multi-scale iterative scheme |
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/173211/21723 |
专题 | 脑图谱与类脑智能实验室_微观重建与智能分析 |
通讯作者 | Han, Hua |
作者单位 | 1.University of Chinese Academy of Sciences, Beijing, China 2.Institute of Automation, Chinese Academy of Sciences, Beijing, China 3.School of Future Technology, University of Chinese Academy of Sciences, Beijing, China 4.The Center for Excellence in Brain Science and Intelligence Technology, CAS, Beijing, China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Shu, Chang,Chen, Xi,Xie, Qiwei,et al. An unsupervised network for fast microscopic image registration[C],2018:105811D. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
An Unsupervised Netw(1167KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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