208 citations · 424 across the 16 of their papers we have counts for
7 papers · 1 filter
CDDSA: Contrastive Domain Disentanglement and Style Augmentation for Generalizable Medical Image Segmentation
Ran Gu, Guotai Wang, Jiangshan Lu +8
Generalization to previously unseen images with potential domain shifts and different styles is essential for clinically applicable medical image segmentation, and the ability to d…
Domain-incremental Cardiac Image Segmentation with Style-oriented Replay and Domain-sensitive Feature Whitening
Kang Li, Lequan Yu, Pheng-Ann Heng
Contemporary methods have shown promising results on cardiac image segmentation, but merely in static learning, i.e., optimizing the network once for all, ignoring potential needs…
Medical Image Understanding with Pretrained Vision Language Models: A Comprehensive Study
Ziyuan Qin, Huahui Yi, Qicheng Lao +1
The large-scale pre-trained vision language models (VLM) have shown remarkable domain transfer capability on natural images. However, it remains unknown whether this capability can…
Contrastive Semi-supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical Structures
Ran Gu, Jingyang Zhang, Guotai Wang +5
Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance for medical image segmentation, yet need plenty of manual annotations for training. Semi-Supervised…
PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation
Guotai Wang, Xiangde Luo, Ran Gu +6
Background and Objective: Open-source deep learning toolkits are one of the driving forces for developing medical image segmentation models. Existing toolkits mainly focus on fully…
PA-Seg: Learning from Point Annotations for 3D Medical Image Segmentation using Contextual Regularization and Cross Knowledge Distillation
Shuwei Zhai, Guotai Wang, Xiangde Luo +3
The success of Convolutional Neural Networks (CNNs) in 3D medical image segmentation relies on massive fully annotated 3D volumes for training that are time-consuming and labor-int…
HMRNet: High and Multi-Resolution Network with Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy
Hao Fu, Guotai Wang, Wenhui Lei +5
Accurate segmentation of Anatomical brain Barriers to Cancer spread (ABCs) plays an important role for automatic delineation of Clinical Target Volume (CTV) of brain tumors in radi…