Guotai Wang

Orcid: 0000-0002-8632-158X

According to our database1, Guotai Wang authored at least 126 papers between 2013 and 2024.

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Bibliography

2024
FPL+: Filtered Pseudo Label-Based Unsupervised Cross-Modality Adaptation for 3D Medical Image Segmentation.
IEEE Trans. Medical Imaging, September, 2024

One-Shot Weakly-Supervised Segmentation in 3D Medical Images.
IEEE Trans. Medical Imaging, January, 2024

Deep learning-based automated steel surface defect segmentation: a comparative experimental study.
Multim. Tools Appl., January, 2024

Semi-supervised pathological image segmentation via cross distillation of multiple attentions and Seg-CAM consistency.
Pattern Recognit., 2024

DMSPS: Dynamically mixed soft pseudo-label supervision for scribble-supervised medical image segmentation.
Medical Image Anal., 2024

Domain composition and attention network trained with synthesized unlabeled images for generalizable medical image segmentation.
Neurocomputing, 2024

LNQ 2023 challenge: Benchmark of weakly-supervised techniques for mediastinal lymph node quantification.
CoRR, 2024

Weakly Supervised Lymph Nodes Segmentation Based on Partial Instance Annotations with Pre-trained Dual-branch Network and Pseudo Label Learning.
CoRR, 2024

VLM-CPL: Consensus Pseudo Labels from Vision-Language Models for Human Annotation-Free Pathological Image Classification.
CoRR, 2024

OpenMEDLab: An Open-source Platform for Multi-modality Foundation Models in Medicine.
CoRR, 2024

SAR-RARP50: Segmentation of surgical instrumentation and Action Recognition on Robot-Assisted Radical Prostatectomy Challenge.
CoRR, 2024

ScribSD+: Scribble-supervised medical image segmentation based on simultaneous multi-scale knowledge distillation and class-wise contrastive regularization.
Comput. Medical Imaging Graph., 2024

IPLC: Iterative Pseudo Label Correction Guided by SAM for Source-Free Domain Adaptation in Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Rethinking Abdominal Organ Segmentation (RAOS) in the Clinical Scenario: A Robustness Evaluation Benchmark with Challenging Cases.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

An Uncertainty-Guided Tiered Self-training Framework for Active Source-Free Domain Adaptation in Prostate Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Self-Supervised Pre-Training Based On Contrastive Complementary Masking for Semi-Supervised Cardiac Image Segmentation.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

SEMI-CONTRANS: Semi-Supervised Medical Image Segmentation via Multi-Scale Feature Fusion and Cross Teaching of CNN and Transformer.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Semi-Supervised Medical Image Segmentation via Multi-Group Network with Consistency Among Heterogeneous Loss Supervision.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

RPL-SFDA: Reliable Pseudo Label-Guided Source-Free Cross-Modality Adaptation for NPC GTV Segmentation.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023
UPL-SFDA: Uncertainty-Aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation.
IEEE Trans. Medical Imaging, December, 2023

Uncertainty-aware and dynamically-mixed pseudo-labels for semi-supervised defect segmentation.
Comput. Ind., November, 2023

HAMIL: High-Resolution Activation Maps and Interleaved Learning for Weakly Supervised Segmentation of Histopathological Images.
IEEE Trans. Medical Imaging, October, 2023

CDDSA: Contrastive domain disentanglement and style augmentation for generalizable medical image segmentation.
Medical Image Anal., October, 2023

Efficient Multi-Organ Segmentation From 3D Abdominal CT Images With Lightweight Network and Knowledge Distillation.
IEEE Trans. Medical Imaging, September, 2023

S<sup>3</sup>R: Shape and Semantics-Based Selective Regularization for Explainable Continual Segmentation Across Multiple Sites.
IEEE Trans. Medical Imaging, September, 2023

MTMVC: Semi-supervised 3D hand pose estimation using multi-task and multi-view consistency.
J. Vis. Commun. Image Represent., September, 2023

A novel one-to-multiple unsupervised domain adaptation framework for abdominal organ segmentation.
Medical Image Anal., August, 2023

Fetal brain tissue annotation and segmentation challenge results.
Medical Image Anal., August, 2023

TISS-net: Brain tumor image synthesis and segmentation using cascaded dual-task networks and error-prediction consistency.
Neurocomputing, August, 2023

PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation.
Comput. Methods Programs Biomed., April, 2023

Multi-Morphological Pulse Signal Feature Point Recognition Based on One-Dimensional Deep Convolutional Neural Network.
Inf., February, 2023

PA-Seg: Learning From Point Annotations for 3D Medical Image Segmentation Using Contextual Regularization and Cross Knowledge Distillation.
IEEE Trans. Medical Imaging, 2023

Contrastive Semi-Supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical Structures.
IEEE Trans. Medical Imaging, 2023

Semisupervised Defect Segmentation With Pairwise Similarity Map Consistency and Ensemble-Based Cross Pseudolabels.
IEEE Trans. Ind. Informatics, 2023

Generalized minimum error entropy for robust learning.
Pattern Recognit., 2023

Editorial for special issue on explainable and generalizable deep learning methods for medical image computing.
Medical Image Anal., 2023

CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation.
Medical Image Anal., 2023

MyoPS: A benchmark of myocardial pathology segmentation combining three-sequence cardiac magnetic resonance images.
Medical Image Anal., 2023

SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma.
CoRR, 2023

UPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation.
CoRR, 2023

MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated Dataset.
CoRR, 2023

Semi-supervised Pathological Image Segmentation via Cross Distillation of Multiple Attentions.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

ScribSD: Scribble-Supervised Fetal MRI Segmentation Based on Simultaneous Feature and Prediction Self-distillation.
Proceedings of the Medical Image Learning with Limited and Noisy Data, 2023

Abdominal Organs and Pan-Cancer Segmentation Based on Self-supervised Pre-training and Self-training.
Proceedings of the Fast, Low-resource, and Accurate Organ and Pan-cancer Segmentation in Abdomen CT, 2023

Scribble-Based 3D Multiple Abdominal Organ Segmentation via Triple-Branch Multi-Dilated Network with Pixel- and Class-Wise Consistency.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

UM-CAM: Uncertainty-weighted Multi-resolution Class Activation Maps for Weakly-supervised Fetal Brain Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Multi-Scale Convolution-Transformer Fusion Network for Endoscopic Image Segmentation.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Fine-Grained Out-of-Distribution Detection of Medical Images using Combination of Feature Uncertainty and Mahalanobis Distance.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Semi-supervised Defect Segmentation with Uncertainty-aware Pseudo-labels from Multi-branch Network.
Proceedings of the 5th International Conference on Image Processing and Machine Vision, 2023

UPL-TTA: Uncertainty-Aware Pseudo Label Guided Fully Test Time Adaptation for Fetal Brain Segmentation.
Proceedings of the Information Processing in Medical Imaging, 2023

2022
Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis From Lung CT Scans With Multi-Scale Guided Dense Attention.
IEEE Trans. Medical Imaging, 2022

Learning COVID-19 Pneumonia Lesion Segmentation From Imperfect Annotations via Divergence-Aware Selective Training.
IEEE J. Biomed. Health Informatics, 2022

HMRNet: High and Multi-Resolution Network With Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy.
IEEE J. Biomed. Health Informatics, 2022

Multiview Video-Based 3-D Pose Estimation of Patients in Computer-Assisted Rehabilitation Environment (CAREN).
IEEE Trans. Hum. Mach. Syst., 2022

Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency.
Medical Image Anal., 2022

SCPM-Net: An anchor-free 3D lung nodule detection network using sphere representation and center points matching.
Medical Image Anal., 2022

WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image.
Medical Image Anal., 2022

MONAI: An open-source framework for deep learning in healthcare.
CoRR, 2022

Contrastive Domain Disentanglement for Generalizable Medical Image Segmentation.
CoRR, 2022

Fetal Brain Tissue Annotation and Segmentation Challenge Results.
CoRR, 2022

CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation.
CoRR, 2022

Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

FPL-UDA: Filtered Pseudo Label-Based Unsupervised Cross-Modality Adaptation for Vestibular Schwannoma Segmentation.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

2021
Annotation-Efficient Learning for Medical Image Segmentation Based on Noisy Pseudo Labels and Adversarial Learning.
IEEE Trans. Medical Imaging, 2021

CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation.
IEEE Trans. Medical Imaging, 2021

Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge.
Medical Image Anal., 2021

MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning.
Medical Image Anal., 2021

Automatic segmentation of gross target volume of nasopharynx cancer using ensemble of multiscale deep neural networks with spatial attention.
Neurocomputing, 2021

Automatic segmentation of organs-at-risk from head-and-neck CT using separable convolutional neural network with hard-region-weighted loss.
Neurocomputing, 2021

One-shot Weakly-Supervised Segmentation in Medical Images.
CoRR, 2021

WORD: Revisiting Organs Segmentation in the Whole Abdominal Region.
CoRR, 2021

2020 CATARACTS Semantic Segmentation Challenge.
CoRR, 2021

Comprehensive Importance-Based Selective Regularization for Continual Segmentation Across Multiple Sites.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Efficient Semi-supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Priori and Posteriori Attention for Generalizing Head and Neck Tumors Segmentation.
Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021

Contrastive Learning of Relative Position Regression for One-Shot Object Localization in 3D Medical Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

LCOV-NET: A Lightweight Neural Network For COVID-19 Pneumonia Lesion Segmentation From 3D CT Images.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

SS-CADA: A Semi-Supervised Cross-Anatomy Domain Adaptation for Coronary Artery Segmentation.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

A Novel Weakly Supervised Framework Based On Noisy-Label Learning For Medical Image Segmentation.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Deep Elastica For Image Segmentation.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

A Denoising Self-supervised Approach for COVID-19 Pneumonia Lesion Segmentation with Limited Annotated CT Images.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Semi-supervised Medical Image Segmentation through Dual-task Consistency.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images.
IEEE Trans. Medical Imaging, 2020

An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI.
NeuroImage, 2020

Automatic ischemic stroke lesion segmentation from computed tomography perfusion images by image synthesis and attention-based deep neural networks.
Medical Image Anal., 2020

Weakly supervised vessel segmentation in X-ray angiograms by self-paced learning from noisy labels with suggestive annotation.
Neurocomputing, 2020

One-Shot Object Localization in Medical Images based on Relative Position Regression.
CoRR, 2020

Semi-supervised Segmentation via Uncertainty Rectified Pyramid Consistency and Its Application to Gross Target Volume of Nasopharyngeal Carcinoma.
CoRR, 2020

Learning Euler's Elastica Model for Medical Image Segmentation.
CoRR, 2020

Semi-supervised Medical Image Segmentation through Dual-task Consistency.
CoRR, 2020

SenseCare: A Research Platform for Medical Image Informatics and Interactive 3D Visualization.
CoRR, 2020

Robust Medical Instrument Segmentation Challenge 2019.
CoRR, 2020

Myocardial Edema and Scar Segmentation Using a Coarse-to-Fine Framework with Weighted Ensemble.
Proceedings of the Myocardial Pathology Segmentation Combining Multi-Sequence Cardiac Magnetic Resonance Images, 2020

Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

CPM-Net: A 3D Center-Points Matching Network for Pulmonary Nodule Detection in CT Scans.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

NAS-SCAM: Neural Architecture Search-Based Spatial and Channel Joint Attention Module for Nuclei Semantic Segmentation and Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

CSAF-CNN: Cross-Layer Spatial Attention Map Fusion Network for Organ-at-Risk Segmentation in Head and Neck CT Images.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Cascaded Coarse-to-Fine Neural Network for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2019
DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks.
Neurocomputing, 2019

Automatic Brain Tumor Segmentation Based on Cascaded Convolutional Neural Networks With Uncertainty Estimation.
Frontiers Comput. Neurosci., 2019

Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss.
CoRR, 2019

High- and Low-Level Feature Enhancement for Medical Image Segmentation.
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

Automated Segmentation of Skin Lesion Based on Pyramid Attention Network.
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

DeepIGeoS-V2: Deep Interactive Segmentation of Multiple Organs from Head and Neck Images with Lightweight CNNs.
Proceedings of the Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention, 2019

Global and Local Multi-scale Feature Fusion Enhancement for Brain Tumor Segmentation and Pancreas Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

Cascaded Global Context Convolutional Neural Network for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018
Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning.
IEEE Trans. Medical Imaging, 2018

Weakly-supervised convolutional neural networks for multimodal image registration.
Medical Image Anal., 2018

NiftyNet: a deep-learning platform for medical imaging.
Comput. Methods Programs Biomed., 2018

Automatic Brain Tumor Segmentation Using Convolutional Neural Networks with Test-Time Augmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018

An Automated Localization, Segmentation and Reconstruction Framework for Fetal Brain MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2017
NiftyNet: a deep-learning platform for medical imaging.
CoRR, 2017

Automatic Brain Tumor Segmentation Using Cascaded Anisotropic Convolutional Neural Networks.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017

On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task.
Proceedings of the Information Processing in Medical Imaging, 2017

2016
Slic-Seg: A minimally interactive segmentation of the placenta from sparse and motion-corrupted fetal MRI in multiple views.
Medical Image Anal., 2016

Dynamically Balanced Online Random Forests for Interactive Scribble-Based Segmentation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

2015
A homotopy-based sparse representation for fast and accurate shape prior modeling in liver surgical planning.
Medical Image Anal., 2015

Slic-Seg: Slice-by-Slice Segmentation Propagation of the Placenta in Fetal MRI Using One-Plane Scribbles and Online Learning.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

2014
Scalable sparse shape composition and its application to liver surgical planning.
Proceedings of the IEEE 11th International Symposium on Biomedical Imaging, 2014

Myocardium segmentation combining T2 and DE MRI using Multi-Component Bivariate Gaussian mixture model.
Proceedings of the IEEE 11th International Symposium on Biomedical Imaging, 2014

2013
Segmentation using Sparse Shape Composition and minimally supervised method in liver surgery planning system.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

An augmented magnetic navigation system for Transcatheter Aortic Valve Implantation.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013


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