Guotai Wang
0000-0002-8632-158X
University of Electronic Science and Technology of China
38 papers found
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PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation
Contrastive Semi-Supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical Structures
WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image
HMRNet: High and Multi-Resolution Network With Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy
Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency
Learning COVID-19 Pneumonia Lesion Segmentation From Imperfect Annotations via Divergence-Aware Selective Training
Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis From Lung CT Scans With Multi-Scale Guided Dense Attention
MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning
Automatic segmentation of organs-at-risk from head-and-neck CT using separable convolutional neural network with hard-region-weighted loss
LCOV-NET: A Lightweight Neural Network For COVID-19 Pneumonia Lesion Segmentation From 3D CT Images
A Novel Weakly Supervised Framework Based On Noisy-Label Learning For Medical Image Segmentation
Efficient Semi-supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency
Comprehensive Importance-Based Selective Regularization for Continual Segmentation Across Multiple Sites
Automatic Segmentation of Gross Target Volume of Nasopharynx Cancer using Ensemble of Multiscale Deep Neural Networks with Spatial Attention
Comparative validation of multi-instance instrument segmentation in endoscopy: results of the ROBUST-MIS 2019 challenge
Weakly Supervised Vessel Segmentation in X-ray Angiograms by Self-Paced Learning from Noisy Labels with Suggestive Annotation
Automatic Ischemic Stroke Lesion Segmentation from Computed Tomography Perfusion Images by Image Synthesis and Attention-Based Deep Neural Networks
CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation
Annotation-Efficient Learning for Medical Image Segmentation based on Noisy Pseudo Labels and Adversarial Learning
NAS-SCAM: Neural Architecture Search-Based Spatial and Channel Joint Attention Module for Nuclei Semantic Segmentation and Classification
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