A survey of medical image registration - under review

By Max A. Viergever, J. B. Antoine Maintz, Stefan Klein, Keelin Murphy, Marius Staring, Josien P. W. Pluim. 2016

286 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Sébastien Ourselin
2. Guotai Wang
3. Tom Kamiel Magda Vercauteren
4. Wenqi Li
5. Dinggang Shen
6. Qian Wang
7. Jun Zhang
8. J. Alison Noble

In Radiology, Nuclear Medicine and Imaging

1. Sébastien Ourselin
2. Guotai Wang
3. Pew-Thian Yap
4. Dinggang Shen
5. Marc Modat
6. Tom Kamiel Magda Vercauteren
7. Qian Wang
8. Jun Zhang

Citations in the corpus

• Deformable Image Registration Using Cue-aware Deep Regression Network (2018, background): “Comprehensive summaries of registration methods can be found in [12]–[19].”
• Weakly-supervised convolutional neural networks for multimodal image registration (2018, methodology): “Manual anatomical feature selection for registration is user-dependent and often costly or even infeasible intraoperatively but arguably remains the most robust method for multimodal image registration for many intra-procedural applications ( Viergever et al., 2016 ).”