CLIP in Medical Imaging: A Comprehensive Survey

1 code implementation • 12 Dec 2023 • Zihao Zhao, Yuxiao Liu, Han Wu, Yonghao Li, Sheng Wang, Lin Teng, Disheng Liu, Zhiming Cui, Qian Wang, Dinggang Shen

With the aim of facilitating a deeper understanding of this promising direction, this survey offers an in-depth exploration of the CLIP paradigm within the domain of medical imaging, regarding both refined CLIP pre-training and CLIP-driven applications.

Multi-scale Transformer Network with Edge-aware Pre-training for Cross-Modality MR Image Synthesis

2 code implementations • 2 Dec 2022 • Yonghao Li, Tao Zhou, Kelei He, Yi Zhou, Dinggang Shen

To take advantage of both paired and unpaired data, in this paper, we propose a Multi-scale Transformer Network (MT-Net) with edge-aware pre-training for cross-modality MR image synthesis.

Image Generation Image Imputation +3

Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks

no code implementations • 4 Sep 2021 • Yiran Wei, Yonghao Li, Xi Chen, Carola-Bibiane Schönlieb, Chao Li, Stephen J. Price

Here we propose a method to predict IDH mutation using GNN, based on the structural brain network of patients.