Localized Region Contrast for Enhancing Self-Supervised Learning in Medical Image Segmentation

no code implementations • 6 Apr 2023 • Xiangyi Yan, Junayed Naushad, Chenyu You, Hao Tang, Shanlin Sun, Kun Han, Haoyu Ma, James Duncan, Xiaohui Xie

In this paper, we propose a novel contrastive learning framework that integrates Localized Region Contrast (LRC) to enhance existing self-supervised pre-training methods for medical image segmentation.

Contrastive Learning Image Segmentation +5

Medical Image Registration via Neural Fields

no code implementations • 7 Jun 2022 • Shanlin Sun, Kun Han, Hao Tang, Deying Kong, Junayed Naushad, Xiangyi Yan, Xiaohui Xie

Traditional methods for image registration are primarily optimization-driven, finding the optimal deformations that maximize the similarity between two images.

Image Registration Medical Image Registration +1

Diffeomorphic Image Registration with Neural Velocity Field

no code implementations • 25 Feb 2022 • Kun Han, Shanlin Sun, Xiangyi Yan, Chenyu You, Hao Tang, Junayed Naushad, Haoyu Ma, Deying Kong, Xiaohui Xie

Here we propose a new optimization-based method named DNVF (Diffeomorphic Image Registration with Neural Velocity Field) which utilizes deep neural network to model the space of admissible transformations.

Image Registration