跳到主要导航 跳到搜索 跳到主要内容

Log-Demons with driving force for large deformation image registration

  • Department of Computer Science and Technology
  • East China Normal University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Capturing large diffeomorphic deformations is difficult for many non-rigid registration methods. In this paper, we propose Log-Demons with driving force for large deformation image registration. The driving force obtained by boundary points correspondence exerts influence on continuous optimization of Log-Demons to improve the motion direction of points. We utilize MROGH descriptor matching to obtain points correspondence as driving force, then the driving force is added to the optimization of Log-Demons. We integrate the driving force in an exponentially decreasing form with velocity field of Log-Demons to drive the points moving globally and to speed up the convergence. Experiments performed on synthetic images, real scene images and brain images demonstrate that the proposed method can not only capture large deformations but also preserve details and register images at a higher accuracy.

源语言英语
主期刊名2016 International Joint Conference on Neural Networks, IJCNN 2016
出版商Institute of Electrical and Electronics Engineers Inc.
页3052-3059
页数8
ISBN(电子版)9781509006199
DOI
出版状态已出版 - 31 10月 2016
活动2016 International Joint Conference on Neural Networks, IJCNN 2016 - Vancouver, 加拿大
期限: 24 7月 2016 → 29 7月 2016

丛书

姓名Proceedings of the International Joint Conference on Neural Networks
卷2016-October

会议

会议2016 International Joint Conference on Neural Networks, IJCNN 2016
国家/地区加拿大
市Vancouver
时期24/07/16 → 29/07/16

学术指纹

探究 'Log-Demons with driving force for large deformation image registration' 的科研主题。它们共同构成独一无二的学术指纹。

引用此