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Deep Learning Representation using Autoencoder for 3D Shape Retrieval

Neurocomputing (Amsterdam), 2016-09, Vol.204, p.41-50

2016

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Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation

Medical image analysis, 2020-10, Vol.65, p.101766-101766, Article 101766

2020

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3D Shape Matching via Two Layer Coding

IEEE transactions on pattern analysis and machine intelligence, 2015-12, Vol.37 (12), p.2361-2373

2015

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Relaxed Multiple-Instance SVM with Application to Object Discovery

2015 IEEE International Conference on Computer Vision (ICCV), 2015, p.1224-1232

2015

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Comprehensive and clinically accurate head and neck cancer organs-at-risk delineation on a multi-institutional study

Nature communications, 2022-10, Vol.13 (1), p.6137-6137, Article 6137

2022

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Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience

Journal of the American College of Radiology, 2019-09, Vol.16 (9), p.1338-1342

2019

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Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-Based Gating Using 3D CT/PET Imaging in Radiotherapy

Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020, Vol.12267, p.753-762

2020

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Editorial: Advances in AI methods for computational pathology

Frontiers in medicine, 2022-09, Vol.9, p.974857-974857

2022

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3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training

2020 IEEE Winter Conference on Applications of Computer Vision (WACV), 2020, p.3635-3644

2020

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Preoperative Prediction of Lymph Node Metastases in Nonfunctional Pancreatic Neuroendocrine Tumors Using a Combined CT Radiomics–Clinical Model

Annals of surgical oncology, 2024-11, Vol.31 (12), p.8136-8145

2024

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ASO Visual Abstract: Preoperative Prediction of Lymph Node Metastases in Nonfunctional Pancreatic Neuroendocrine Tumors Using a Combined CT Radiomics-Clinical Model

Annals of surgical oncology, 2024-09, Vol.31 (13), p.9014-9015

2024

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Organ at Risk Segmentation for Head and Neck Cancer Using Stratified Learning and Neural Architecture Search

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, p.4222-4231

2020

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Bridging the Gap Between 2D and 3D Organ Segmentation with Volumetric Fusion Net

Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018, Vol.11073, p.445-453

2018

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Deep neural network-based segmentation of normal and abnormal pancreas on abdominal CT: evaluation of global and local accuracies

Abdominal radiology (New York), 2024-02, Vol.49 (2), p.501-511

2024

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Accurate non-invasive grading of nonfunctional pancreatic neuroendocrine tumors with a CT derived radiomics signature

Diagnostic and interventional imaging, 2024-01, Vol.105 (1), p.33-39

2024

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Segmentation for Classification of Screening Pancreatic Neuroendocrine Tumors

2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021, p.3395-3401

2021

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V-NAS: Neural Architecture Search for Volumetric Medical Image Segmentation

2019 International Conference on 3D Vision (3DV), 2019, p.240-248

2019

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Deep learning representation using autoencoder for 3D shape retrieval

Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), 2014, p.279-284

2014

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ImageNet Classification with Complementary Networks

Zhu, Zhuotun

2016

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Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-Fine Framework and Its Adversarial Examples

Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics, 2019, p.69-91

2019

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A 3D Coarse-to-Fine Framework for Volumetric Medical Image Segmentation

2018 International Conference on 3D Vision (3DV), 2018, p.682-690

2018

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Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network

Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020, Vol.12267, p.772-782

2020

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Thoracic Lymph Node Segmentation in CT Imaging via Lymph Node Station Stratification and Size Encoding

Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022, Vol.13435, p.55-65

2022

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Multi-scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma

Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019, Vol.11769, p.3-12

2019

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Deep Learning Representation using Autoencoder for 3D Shape Retrieval

Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation

3D Shape Matching via Two Layer Coding

Relaxed Multiple-Instance SVM with Application to Object Discovery

Comprehensive and clinically accurate head and neck cancer organs-at-risk delineation on a multi-institutional study

Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience

Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-Based Gating Using 3D CT/PET Imaging in Radiotherapy

Editorial: Advances in AI methods for computational pathology

3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training

Preoperative Prediction of Lymph Node Metastases in Nonfunctional Pancreatic Neuroendocrine Tumors Using a Combined CT Radiomics–Clinical Model

ASO Visual Abstract: Preoperative Prediction of Lymph Node Metastases in Nonfunctional Pancreatic Neuroendocrine Tumors Using a Combined CT Radiomics-Clinical Model

Organ at Risk Segmentation for Head and Neck Cancer Using Stratified Learning and Neural Architecture Search

Bridging the Gap Between 2D and 3D Organ Segmentation with Volumetric Fusion Net

Deep neural network-based segmentation of normal and abnormal pancreas on abdominal CT: evaluation of global and local accuracies

Accurate non-invasive grading of nonfunctional pancreatic neuroendocrine tumors with a CT derived radiomics signature

Segmentation for Classification of Screening Pancreatic Neuroendocrine Tumors

V-NAS: Neural Architecture Search for Volumetric Medical Image Segmentation

Deep learning representation using autoencoder for 3D shape retrieval

ImageNet Classification with Complementary Networks

Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-Fine Framework and Its Adversarial Examples

A 3D Coarse-to-Fine Framework for Volumetric Medical Image Segmentation

Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network

Thoracic Lymph Node Segmentation in CT Imaging via Lymph Node Station Stratification and Size Encoding

Multi-scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma

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