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20202025
most citedPanoptic Feature Fusion Net: A Novel Instance Segmentation Paradigm for Biomedical and Biological Images

67 citations · 140 across the 48 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

eess.IV2022

TW-BAG: Tensor-wise Brain-aware Gate Network for Inpainting Disrupted Diffusion Tensor Imaging

Zihao Tang, Xinyi Wang, Lihaowen Zhu +5

Diffusion Weighted Imaging (DWI) is an advanced imaging technique commonly used in neuroscience and neurological clinical research through a Diffusion Tensor Imaging (DTI) model. V…

cs.CV2022★ 1 cited

Unsupervised Domain Adaptive Fundus Image Segmentation with Few Labeled Source Data

Qianbi Yu, Dongnan Liu, Chaoyi Zhang +2

Deep learning-based segmentation methods have been widely employed for automatic glaucoma diagnosis and prognosis. In practice, fundus images obtained by different fundus cameras v…

cs.CV2022

Domain Adaptive Nuclei Instance Segmentation and Classification via Category-aware Feature Alignment and Pseudo-labelling

Canran Li, Dongnan Liu, Haoran Li +4

Unsupervised domain adaptation (UDA) methods have been broadly utilized to improve the models' adaptation ability in general computer vision. However, different from the natural im…

eess.IV2022★ 1 cited

MS Lesion Segmentation: Revisiting Weighting Mechanisms for Federated Learning

Dongnan Liu, Mariano Cabezas, Dongang Wang +16

Federated learning (FL) has been widely employed for medical image analysis to facilitate multi-client collaborative learning without sharing raw data. Despite great success, FL's…

cs.CV2022

Towards Bi-directional Skip Connections in Encoder-Decoder Architectures and Beyond

Tiange Xiang, Chaoyi Zhang, Xinyi Wang +4

U-Net, as an encoder-decoder architecture with forward skip connections, has achieved promising results in various medical image analysis tasks. Many recent approaches have also ex…

cs.CV2022★ 2 cited

Decompose to Adapt: Cross-domain Object Detection via Feature Disentanglement

Dongnan Liu, Chaoyi Zhang, Yang Song +4

Recent advances in unsupervised domain adaptation (UDA) techniques have witnessed great success in cross-domain computer vision tasks, enhancing the generalization ability of data-…