PhD Student Tony Chi Wing Mok Awarded First Place in MICCAI Learn2Reg 2020 Challenge

Applying the method mentioned in his paper titled "Large Deformation Diffeomorphic Image Registration with Laplacian Pyramid Networks" co-authored with, Prof. Albert Chung, Professor of Computer Science and Engineering and Associate Dean of Engineering (Undergraduate Studies), CSE PhD student Tony Chi Wing Mok achieved First Place in the MICCAI Learn2Reg 2020 challenge.

Learn2Reg challenge is a medical image registration challenge organized by The Medical Image Computing and Computer Assisted Intervention Society (MICCAI), which was built on the Learn2Reg tutorial in 2019 with a simplified design that removes many of the common pitfalls for learning and applying transformations.

In their paper, they have presented a novel Deep Laplacian Pyramid Image Registration Network for large deformation image registration with a new similarity pyramid, which mimics the conventional multi-resolution strategy to capture misalignments between input scans. To guarantee desirable diffeomorphic properties of deformation fields, they formulated their method with diffeomorphism using the stationary vector fields under the Log-Euclidean framework.

Congratulations to Tony!

For more details, please refer to the event website.

Tony Chi Wing Mok (left) and Prof. Albert Chung

Tony Chi Wing Mok (left) and Prof. Albert Chung

Announcement by MICCAI Learn2Reg 2020 Challenge

Announcement by MICCAI Learn2Reg 2020 Challenge

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