Yaozong Gao

According to our database1, Yaozong Gao authored at least 87 papers between 2012 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2019
STRAINet: Spatially Varying sTochastic Residual AdversarIal Networks for MRI Pelvic Organ Segmentation.
IEEE Trans. Neural Netw. Learning Syst., 2019

CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation.
Medical Image Analysis, 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

Automatic MR kidney segmentation for autosomal dominant polycystic kidney disease.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019

Hierarchical Representation For Ct Prostate Segmentation.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Segmentation of CT Thoracic Organs by Multi-resolution VB-nets.
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 Processing, 2018

Region-Adaptive Deformable Registration of CT/MRI Pelvic Images via Learning-Based Image Synthesis.
IEEE Trans. Image Processing, 2018

Segmenting hippocampal subfields from 3T MRI with multi-modality images.
Medical Image Analysis, 2018

Robust brain ROI segmentation by deformation regression and deformable shape model.
Medical Image Analysis, 2018

Malignant Brain Tumor Classification Using the Random Forest Method.
Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2018

Fine-Grained Segmentation Using Hierarchical Dilated Neural Networks.
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

Multimodal Brain Tumor Segmentation Using Cascaded V-Nets.
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. Biomedical and Health Informatics, 2017

Structured Learning for 3-D Perivascular Space Segmentation Using Vascular Features.
IEEE Trans. Biomed. Engineering, 2017

Dual-core steered non-rigid registration for multi-modal images via bi-directional image synthesis.
Medical Image Analysis, 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
Detecting Anatomical Landmarks for Fast Alzheimer's Disease Diagnosis.
IEEE Trans. Med. Imaging, 2016

Estimating CT Image From MRI Data Using Structured Random Forest and Auto-Context Model.
IEEE Trans. Med. Imaging, 2016

Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching.
IEEE Trans. Med. Imaging, 2016

Accurate Segmentation of CT Male Pelvic Organs via Regression-Based Deformable Models and Multi-Task Random Forests.
IEEE Trans. Med. Imaging, 2016

Automatic Craniomaxillofacial Landmark Digitization via Segmentation-Guided Partially-Joint Regression Forest Model and Multiscale Statistical Features.
IEEE Trans. Biomed. Engineering, 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.
Comp. Med. Imag. and Graph., 2016

In vivo MRI based prostate cancer localization with random forests and auto-context model.
Comp. Med. Imag. and 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

Regression Guided Deformable Models for Segmentation of Multiple Brain ROIs.
Proceedings of the Machine Learning in Medical Imaging - 7th International Workshop, 2016

Automatic Hippocampal Subfield Segmentation from 3T Multi-modality Images.
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

Estimating CT Image from MRI Data Using 3D Fully Convolutional Networks.
Proceedings of the Deep Learning and Data Labeling for Medical Applications, 2016

Automatic Cystocele Severity Grading in Ultrasound by Spatio-Temporal Regression.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

Learning-Based Multimodal Image Registration for Prostate Cancer Radiation Therapy.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

7T-Guided Learning Framework for Improving the Segmentation of 3T MR Images.
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

Locally-constrained boundary regression for segmentation of prostate and rectum in the planning CT images.
Medical Image Analysis, 2015

A transversal approach for patch-based label fusion via matrix completion.
Medical Image Analysis, 2015

Robust anatomical landmark detection with application to MR brain image registration.
Comp. Med. Imag. and Graph., 2015

Dynamic Tree-Based Large-Deformation Image Registration for Multi-atlas Segmentation.
Proceedings of the Medical Computer Vision: Algorithms for Big Data, 2015

Automatic Hippocampus Labeling Using the Hierarchy of Sub-region Random Forests.
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

Hippocampus Segmentation from MR Infant Brain Images via Boundary Regression.
Proceedings of the Medical Computer Vision: Algorithms for Big Data, 2015

Multi-atlas Based Segmentation Editing with Interaction-Guided Constraints.
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

Non-local Atlas-guided Multi-channel Forest Learning for Human Brain Labeling.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

Soft-Split Random Forest for Anatomy Labeling.
Proceedings of the Machine Learning in Medical Imaging - 6th International Workshop, 2015

Multi-atlas Context Forests for Knee MR Image Segmentation.
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

Automated Segmentation of CBCT Image with Prior-Guided Sequential Random Forest.
Proceedings of the Medical Computer Vision: Algorithms for Big Data, 2015

Automatic parcellation of cortical surfaces using random forests.
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. Med. Imaging, 2014

Correction to "Learning to Rank Atlases for Multiple-Atlas Segmentation".
IEEE Trans. Med. Imaging, 2014

Learning to Rank Atlases for Multiple-Atlas Segmentation.
IEEE Trans. Med. Imaging, 2014

Segmentation of neonatal brain MR images using patch-driven level sets.
NeuroImage, 2014

Integration of sparse multi-modality representation and anatomical constraint for isointense infant brain MR image segmentation.
NeuroImage, 2014

Learning of Atlas Forest Hierarchy for Automatic Labeling of MR Brain Images.
Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014

CT Prostate Deformable Segmentation by Boundary Regression.
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

Atlas-Guided Multi-channel Forest Learning for Human Brain Labeling.
Proceedings of the Medical Computer Vision: Algorithms for Big Data, 2014

Prediction of Standard-Dose PET Image by Low-Dose PET and MRI Images.
Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014

Robust Anatomical Landmark Detection for MR Brain Image Registration.
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

LINKS: Learning-Based Multi-source IntegratioN FrameworK for Segmentation of Infant Brain Images.
Proceedings of the Medical Computer Vision: Algorithms for Big Data, 2014

Learning-Based Atlas Selection for Multiple-Atlas Segmentation.
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. Med. Imaging, 2013

Unsupervised Deep Feature Learning for Deformable Registration of MR Brain Images.
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

Incremental Learning with Selective Memory (ILSM): Towards Fast Prostate Localization for Image Guided Radiotherapy.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013

MR prostate segmentation via distributed discriminative dictionary (DDD) learning.
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

Prostate Segmentation in CT Images via Spatial-Constrained Transductive Lasso.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012
Transductive Prostate Segmentation for CT Image Guided Radiotherapy.
Proceedings of the Machine Learning in Medical Imaging - Third International Workshop, 2012

Sparse Patch Based Prostate Segmentation in CT Images.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Prostate Segmentation by Sparse Representation Based Classification.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012


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