Gaze-DETR: Using Expert Gaze to Reduce False Positives in Vulvovaginal Candidiasis Screening

1 code implementation • 15 May 2024 • Yan Kong, Sheng Wang, Jiangdong Cai, Zihao Zhao, Zhenrong Shen, Yonghao Li, Manman Fei, Qian Wang

Accurate detection of vulvovaginal candidiasis is critical for women's health, yet its sparse distribution and visually ambiguous characteristics pose significant challenges for accurate identification by pathologists and neural networks alike.

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.