Yaozong Gao
Orcid: 0000-0002-7547-5209
According to our database1,
Yaozong Gao
authored at least 113 papers
between 2012 and 2023.
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Bibliography
2023
Structural Attention Graph Neural Network for Diagnosis and Prediction of COVID-19 Severity.
IEEE Trans. Medical Imaging, February, 2023
2022
IEEE Trans. Medical Imaging, 2022
Semi-Supervised Deep Transfer Learning for Benign-Malignant Diagnosis of Pulmonary Nodules in Chest CT Images.
IEEE Trans. Medical Imaging, 2022
Weakly Supervised Segmentation of COVID19 Infection with Scribble Annotation on CT Images.
Pattern Recognit., 2022
Clinical evaluation of deep learning-based clinical target volume three-channel auto-segmentation algorithm for adaptive radiotherapy in cervical cancer.
BMC Medical Imaging, 2022
LA-Net: Lung Adenocarcinoma Classification with Assistants from Lung Nodule Classification and Positional Information.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022
2021
Joint prediction and time estimation of COVID-19 developing severe symptoms using chest CT scan.
Medical Image Anal., 2021
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge.
Medical Image Anal., 2021
Medical Image Anal., 2021
CoRR, 2021
A cascade and heterogeneous neural network for CT pulmonary nodule detection and its evaluation on both phantom and patient data.
Comput. Medical Imaging Graph., 2021
An artificial-intelligence lung imaging analysis system (ALIAS) for population-based nodule computing in CT scans.
Comput. Medical Imaging Graph., 2021
Computing infection distributions and longitudinal evolution patterns in lung CT images.
BMC Medical Imaging, 2021
2020
IEEE Trans. Medical Imaging, 2020
Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia.
IEEE Trans. Medical Imaging, 2020
Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT.
IEEE J. Biomed. Health Informatics, 2020
Frontiers Comput. Neurosci., 2020
Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification with Chest CT.
CoRR, 2020
Large-Scale Screening of COVID-19 from Community Acquired Pneumonia using Infection Size-Aware Classification.
CoRR, 2020
CoRR, 2020
Two-Stage Mapping-Segmentation Framework for Delineating COVID-19 Infections from Heterogeneous CT Images.
Proceedings of the Thoracic Image Analysis - Second International Workshop, 2020
Semantic Hierarchy Guided Registration Networks for Intra-subject Pulmonary CT Image Alignment.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2019
STRAINet: Spatially Varying sTochastic Residual AdversarIal Networks for MRI Pelvic Organ Segmentation.
IEEE Trans. Neural Networks Learn. Syst., 2019
CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation.
Medical Image Anal., 2019
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge.
CoRR, 2019
Hippocampal Segmentation From Longitudinal Infant Brain MR Images via Classification-Guided Boundary Regression.
IEEE Access, 2019
Large-scale evaluation of V-Net for organ segmentation in image guided radiation therapy.
Proceedings of the Medical Imaging 2019: Image-Guided Procedures, 2019
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019
Proceedings of the 2019 Challenge on Segmentation of THoracic Organs at Risk in CT Images, 2019
2018
Hierarchical Vertex Regression-Based Segmentation of Head and Neck CT Images for Radiotherapy Planning.
IEEE Trans. Image Process., 2018
Region-Adaptive Deformable Registration of CT/MRI Pelvic Images via Learning-Based Image Synthesis.
IEEE Trans. Image Process., 2018
Medical Image Anal., 2018
Medical Image Anal., 2018
Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2018
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
ASDNet: Attention Based Semi-supervised Deep Networks for Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018
2017
Alzheimer's Disease Diagnosis Using Landmark-Based Features From Longitudinal Structural MR Images.
IEEE J. Biomed. Health Informatics, 2017
IEEE Trans. Biomed. Eng., 2017
Dual-core steered non-rigid registration for multi-modal images via bi-directional image synthesis.
Medical Image Anal., 2017
Concatenated spatially-localized random forests for hippocampus labeling in adult and infant MR brain images.
Neurocomputing, 2017
Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching.
Proceedings of the Deep Learning for Medical Image Analysis, 1st Edition, 2017
2016
Accurate Segmentation of CT Pelvic Organs via Incremental Cascade Learning and Regression-based Deformable Models.
PhD thesis, 2016
IEEE Trans. Medical Imaging, 2016
Estimating CT Image From MRI Data Using Structured Random Forest and Auto-Context Model.
IEEE Trans. Medical Imaging, 2016
Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching.
IEEE Trans. Medical Imaging, 2016
Accurate Segmentation of CT Male Pelvic Organs via Regression-Based Deformable Models and Multi-Task Random Forests.
IEEE Trans. Medical Imaging, 2016
Automatic Craniomaxillofacial Landmark Digitization via Segmentation-Guided Partially-Joint Regression Forest Model and Multiscale Statistical Features.
IEEE Trans. Biomed. Eng., 2016
Segmentation of perivascular spaces in 7 T MR image using auto-context model with orientation-normalized features.
NeuroImage, 2016
A learning-based CT prostate segmentation method via joint transductive feature selection and regression.
Neurocomputing, 2016
A dynamic tree-based registration could handle possible large deformations among MR brain images.
Comput. Medical Imaging Graph., 2016
In vivo MRI based prostate cancer localization with random forests and auto-context model.
Comput. Medical Imaging Graph., 2016
Landmark-Based Alzheimer's Disease Diagnosis Using Longitudinal Structural MR Images.
Proceedings of the Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging, 2016
Segmentation of Perivascular Spaces Using Vascular Features and Structured Random Forest from 7T MR Image.
Proceedings of the Machine Learning in Medical Imaging - 7th International Workshop, 2016
Proceedings of the Machine Learning in Medical Imaging - 7th International Workshop, 2016
Proceedings of the Machine Learning in Medical Imaging - 7th International Workshop, 2016
Learning Appearance and Shape Evolution for Infant Image Registration in the First Year of Life.
Proceedings of the Machine Learning in Medical Imaging - 7th International Workshop, 2016
LATEST: Local AdapTivE and Sequential Training for Tissue Segmentation of Isointense Infant Brain MR Images.
Proceedings of the Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging, 2016
Proceedings of the Deep Learning and Data Labeling for Medical Applications, 2016
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
Fully convolutional networks for multi-modality isointense infant brain image segmentation.
Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016
2015
Semi-Automatic Segmentation of Prostate in CT Images via Coupled Feature Representation and Spatial-Constrained Transductive Lasso.
IEEE Trans. Pattern Anal. Mach. Intell., 2015
LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.
NeuroImage, 2015
Locally-constrained boundary regression for segmentation of prostate and rectum in the planning CT images.
Medical Image Anal., 2015
Medical Image Anal., 2015
Robust anatomical landmark detection with application to MR brain image registration.
Comput. Medical Imaging Graph., 2015
Dynamic Tree-Based Large-Deformation Image Registration for Multi-atlas Segmentation.
Proceedings of the Medical Computer Vision: Algorithms for Big Data, 2015
Proceedings of the Patch-Based Techniques in Medical Imaging, 2015
Automatic Craniomaxillofacial Landmark Digitization via Segmentation-Guided Partially-Joint Regression Forest Model.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015
Isointense Infant Brain Segmentation by Stacked Kernel Canonical Correlation Analysis.
Proceedings of the Patch-Based Techniques in Medical Imaging, 2015
Proceedings of the Medical Computer Vision: Algorithms for Big Data, 2015
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015
Subject-Specific Estimation of Missing Cortical Thickness Maps in Developing Infant Brains.
Proceedings of the Medical Computer Vision: Algorithms for Big Data, 2015
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015
Proceedings of the Machine Learning in Medical Imaging - 6th International Workshop, 2015
Proceedings of the Machine Learning in Medical Imaging - 6th International Workshop, 2015
Multi-source Information Gain for Random Forest: An Application to CT Image Prediction from MRI Data.
Proceedings of the Machine Learning in Medical Imaging - 6th International Workshop, 2015
Soft-Split Sparse Regression Based Random Forest for Predicting Future Clinical Scores of Alzheimer's Disease.
Proceedings of the Machine Learning in Medical Imaging - 6th International Workshop, 2015
Hierarchical Multi-modal Image Registration by Learning Common Feature Representations.
Proceedings of the Machine Learning in Medical Imaging - 6th International Workshop, 2015
Joint Learning of Image Regressor and Classifier for Deformable Segmentation of CT Pelvic Organs.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015
Proceedings of the Medical Computer Vision: Algorithms for Big Data, 2015
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015
2014
Hierarchical Lung Field Segmentation With Joint Shape and Appearance Sparse Learning.
IEEE Trans. Medical Imaging, 2014
IEEE Trans. Medical Imaging, 2014
IEEE Trans. Medical Imaging, 2014
Incremental Learning With Selective Memory (ILSM): Towards Fast Prostate Localization for Image Guided Radiotherapy.
IEEE Trans. Medical Imaging, 2014
NeuroImage, 2014
Integration of sparse multi-modality representation and anatomical constraint for isointense infant brain MR image segmentation.
NeuroImage, 2014
Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014
Proceedings of the Medical Computer Vision: Algorithms for Big Data, 2014
Estimating Anatomically-Correct Reference Model for Craniomaxillofacial Deformity via Sparse Representation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014
Interactive Prostate Segmentation Based on Adaptive Feature Selection and Manifold Regularization.
Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014
Proceedings of the Medical Computer Vision: Algorithms for Big Data, 2014
Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014
Learning Distance Transform for Boundary Detection and Deformable Segmentation in CT Prostate Images.
Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014
Context-Aware Anatomical Landmark Detection: Application to Deformable Model Initialization in Prostate CT Images.
Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014
2013
Sparse Patch-Based Label Propagation for Accurate Prostate Localization in CT Images.
IEEE Trans. Medical Imaging, 2013
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013
Automated Segmentation of CBCT Image Using Spiral CT Atlases and Convex Optimization.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013
Representation Learning: A Unified Deep Learning Framework for Automatic Prostate MR Segmentation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013
Automatic Prostate MR Image Segmentation with Sparse Label Propagation and Domain-Specific Manifold Regularization.
Proceedings of the Information Processing in Medical Imaging, 2013
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013
2012
Proceedings of the Machine Learning in Medical Imaging - Third International Workshop, 2012
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012