首页> Medical image analysis> A robust and interpretable deep learning framework for multi-modal registration via keypoints.

A robust and interpretable deep learning framework for multi-modal registration via keypoints.

导出 OA

翻译打印收藏纠错

第一作者： Alan Q,Wang

第一单位： School of Electrical and Computer Engineering, Cornell University and Cornell Tech, New York, NY 10044, USA; Department of Radiology, Weill Cornell Medical School, New York, NY 10065, USA. Electronic address: aw847@cornell.edu.

作者： Alan Q,Wang ^[1] ; Evan M,Yu ^[2] ; Adrian V,Dalca ^[3] ; Mert R,Sabuncu ^[4]

作者单位： School of Electrical and Computer Engineering, Cornell University and Cornell Tech, New York, NY 10044, USA; Department of Radiology, Weill Cornell Medical School, New York, NY 10065, USA. Electronic address: aw847@cornell.edu. ^[1] Iterative Scopes, Cambridge, MA 02139, USA. ^[2] Computer Science and Artificial Intelligence Lab at the Massachusetts Institute of Technology, Cambridge, MA 02139, USA; A.A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital, Charlestown, MA 02129, USA. ^[3] School of Electrical and Computer Engineering, Cornell University and Cornell Tech, New York, NY 10044, USA; Department of Radiology, Weill Cornell Medical School, New York, NY 10065, USA. ^[4]

关键词 Image registration Keypoint detection Multi-modal

医学主题词人类(Humans);脑(Brain);磁共振成像(Magnetic Resonance Imaging);图像处理, 计算机辅助(Image Processing, Computer-Assisted)

DOI 10.1016/j.media.2023.102962

PMID 37769550

发布时间 2026-03-07

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交