96 citations · 464 across the 30 of their papers we have counts for
5 papers · 1 filter
TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers
Di Liu, Yunhe Gao, Qilong Zhangli +8
Combining information from multi-view images is crucial to improve the performance and robustness of automated methods for disease diagnosis. However, due to the non-alignment char…
A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark
Yunhe Gao, Mu Zhou, Di Liu +3
Transformers have demonstrated remarkable performance in natural language processing and computer vision. However, existing vision Transformers struggle to learn from limited medic…
Modality Bank: Learn multi-modality images across data centers without sharing medical data
Qi Chang, Hui Qu, Zhennan Yan +3
Multi-modality images have been widely used and provide comprehensive information for medical image analysis. However, acquiring all modalities among all institutes is costly and o…
FocusNetv2: Imbalanced Large and Small Organ Segmentation with Adversarial Shape Constraint for Head and Neck CT Images
Yunhe Gao, Rui Huang, Yiwei Yang +7
Radiotherapy is a treatment where radiation is used to eliminate cancer cells. The delineation of organs-at-risk (OARs) is a vital step in radiotherapy treatment planning to avoid…
FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images
Yunhe Gao, Rui Huang, Ming Chen +7
In this paper, we propose an end-to-end deep neural network for solving the problem of imbalanced large and small organ segmentation in head and neck (HaN) CT images. To conduct ra…