1.3k citations · 2k across the 59 of their papers we have counts for
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Lesion Guided Explainable Few Weak-shot Medical Report Generation
Jinghan Sun, Dong Wei, Liansheng Wang +1
Medical images are widely used in clinical practice for diagnosis. Automatically generating interpretable medical reports can reduce radiologists' burden and facilitate timely care…
Dual Multi-scale Mean Teacher Network for Semi-supervised Infection Segmentation in Chest CT Volume for COVID-19
Liansheng Wang, Jiacheng Wang, Lei Zhu +6
Automated detecting lung infections from computed tomography (CT) data plays an important role for combating COVID-19. However, there are still some challenges for developing AI sy…
UNet-2022: Exploring Dynamics in Non-isomorphic Architecture
Jiansen Guo, Hong-Yu Zhou, Liansheng Wang +1
Recent medical image segmentation models are mostly hybrid, which integrate self-attention and convolution layers into the non-isomorphic architecture. However, one potential drawb…
Personalizing Federated Medical Image Segmentation via Local Calibration
Jiacheng Wang, Yueming Jin, Liansheng Wang
Medical image segmentation under federated learning (FL) is a promising direction by allowing multiple clinical sites to collaboratively learn a global model without centralizing d…
A New Dataset and A Baseline Model for Breast Lesion Detection in Ultrasound Videos
Zhi Lin, Junhao Lin, Lei Zhu +3
Breast lesion detection in ultrasound is critical for breast cancer diagnosis. Existing methods mainly rely on individual 2D ultrasound images or combine unlabeled video and labele…
XBound-Former: Toward Cross-scale Boundary Modeling in Transformers
Jiacheng Wang, Fei Chen, Yuxi Ma +6
Skin lesion segmentation from dermoscopy images is of great significance in the quantitative analysis of skin cancers, which is yet challenging even for dermatologists due to the i…
Learning Shape Priors by Pairwise Comparison for Robust Semantic Segmentation
Cong Xie, Hualuo Liu, Shilei Cao +4
Semantic segmentation is important in medical image analysis. Inspired by the strong ability of traditional image analysis techniques in capturing shape priors and inter-subject si…
CholecTriplet2021: A benchmark challenge for surgical action triplet recognition
Chinedu Innocent Nwoye, Deepak Alapatt, Tong Yu +59
Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works…
Conquering Data Variations in Resolution: A Slice-Aware Multi-Branch Decoder Network
Shuxin Wang, Shilei Cao, Zhizhong Chai +4
Fully convolutional neural networks have made promising progress in joint liver and liver tumor segmentation. Instead of following the debates over 2D versus 3D networks (for examp…
Simultaneous Alignment and Surface Regression Using Hybrid 2D-3D Networks for 3D Coherent Layer Segmentation of Retina OCT Images
Hong Liu, Dong Wei, Donghuan Lu +4
Automated surface segmentation of retinal layer is important and challenging in analyzing optical coherence tomography (OCT). Recently, many deep learning based methods have been d…