iRegNet: Non-Rigid Registration of MRI to Interventional US for Brain-Shift Compensation Using Convolutional Neural Networks

iRegNet: Non-Rigid Registration of MRI to Interventional US for Brain-Shift Compensation Using Convolutional Neural Networks

Accurate and safe neurosurgical intervention can be affected by intra-operative tissue deformation, known as brain-shift. In this study, we propose an automatic, fast, and accurate deformable method, called iRegNet, for registering pre-operative magnetic resonance images to intra-operative ultrasoun...

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Bibliographic Details
Main Authors: Ramy A. Zeineldin, Mohamed E. Karar, Ziad Elshaer, Markus Schmidhammer, Jan Coburger, Christian R. Wirtz, Oliver Burgert, Franziska Mathis-Ullrich
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Brain-Shift
computer-aided diagnosis
medical image registration
neurosurgery
intra-operative ultrasound
Online Access:https://ieeexplore.ieee.org/document/9570282/

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