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20202026
most citedUPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation

61 citations · 68 across the 7 of their papers we have counts for

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5 papers · 1 filter

eess.IV2021

Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation

Ran Gu, Jingyang Zhang, Rui Huang +3

Domain generalizable model is attracting increasing attention in medical image analysis since data is commonly acquired from different institutes with various imaging protocols and…

eess.IV2021

SS-CADA: A Semi-Supervised Cross-Anatomy Domain Adaptation for Coronary Artery Segmentation

Jingyang Zhang, Ran Gu, Guotai Wang +2

The segmentation of coronary arteries by convolutional neural network is promising yet requires a large amount of labor-intensive manual annotations. Transferring knowledge from re…

eess.IV20214 cited

Automatic Segmentation of Organs-at-Risk from Head-and-Neck CT using Separable Convolutional Neural Network with Hard-Region-Weighted Loss

Wenhui Lei, Haochen Mei, Zhengwentai Sun +7

Nasopharyngeal Carcinoma (NPC) is a leading form of Head-and-Neck (HAN) cancer in the Arctic, China, Southeast Asia, and the Middle East/North Africa. Accurate segmentation of Orga…

eess.IV2021

Automatic Segmentation of Gross Target Volume of Nasopharynx Cancer using Ensemble of Multiscale Deep Neural Networks with Spatial Attention

Haochen Mei, Wenhui Lei, Ran Gu +4

Radiotherapy is the main treatment modality for nasopharynx cancer. Delineation of Gross Target Volume (GTV) from medical images such as CT and MRI images is a prerequisite for rad…

eess.IV2020

CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation

Ran Gu, Guotai Wang, Tao Song +6

Accurate medical image segmentation is essential for diagnosis and treatment planning of diseases. Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance f…