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Automatic Liver Segmentation Using an Adversarial Image-to-Image Network

Medical Image Computing and Computer Assisted Intervention − MICCAI 2017, p.507-515

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Machine learning automatically detects COVID-19 using chest CTs in a large multicenter cohort

European radiology, 2021-11, Vol.31 (11), p.8775-8785

2021

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AUCReshaping: improved sensitivity at high-specificity

Scientific reports, 2023-11, Vol.13 (1), p.21097-21097, Article 21097

2023

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A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation

Radiation oncology (London, England), 2022-07, Vol.17 (1), p.1-129, Article 129

2022

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Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings

Korean Journal of Radiology, 2021, 22(6), , pp.994-1004

2021

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Correction: A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation

Radiation oncology (London, England), 2022-08, Vol.17 (1), p.1-149, Article 149

2022

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Class-Aware Adversarial Lung Nodule Synthesis In CT Images

2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 2019, p.1348-1352

2019

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Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans

IEEE transactions on pattern analysis and machine intelligence, 2019-01, Vol.41 (1), p.176-189

2019

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COSST: Multi-Organ Segmentation With Partially Labeled Datasets Using Comprehensive Supervisions and Self-Training

IEEE transactions on medical imaging, 2024-05, Vol.43 (5), p.1995-2009

2024

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Towards intelligent robust detection of anatomical structures in incomplete volumetric data

Medical image analysis, 2018-08, Vol.48, p.203-213

2018

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No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting With Adversarial Attacks

IEEE transactions on medical imaging, 2021-01, Vol.40 (1), p.335-345

2021

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3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes

Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, p.851-858

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Automated Detection and Quantification of COVID-19 Airspace Disease on Chest Radiographs: A Novel Approach Achieving Expert Radiologist-Level Performance Using a Deep Convolutional Neural Network Trained on Digital Reconstructed Radiographs From Computed Tomography-Derived Ground Truth

Investigative radiology, 2021-08, Vol.56 (8), p.471-479

2021

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Quantifying and leveraging predictive uncertainty for medical image assessment

Medical image analysis, 2021-02, Vol.68, p.101855-101855, Article 101855

2021

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Semiautomatically Quantified Tumor Volume Using 68 Ga-PSMA-11 PET as a Biomarker for Survival in Patients with Advanced Prostate Cancer

Journal of Nuclear Medicine, 2020-12, Vol.61 (12), p.1786-1792

2020

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Semiautomatically Quantified Tumor Volume Using 68Ga-PSMA-11 PET as a Biomarker for Survival in Patients with Advanced Prostate Cancer

The Journal of nuclear medicine (1978), 2020-12, Vol.61 (12), p.1786-1792

2020

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Robust classification from noisy labels: Integrating additional knowledge for chest radiography abnormality assessment

Medical image analysis, 2021-08, Vol.72, p.102087-102087, Article 102087

2021

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Detection and characterization of COVID-19 findings in chest CT: Feasibility and applicability of an AI-based software tool

Medicine (Baltimore), 2021-10, Vol.100 (41), p.e27478-e27478

2021

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Automated Quantification of CT Patterns Associated with COVID-19 from Chest CT

Radiology. Artificial intelligence, 2020-07, Vol.2 (4), p.e200048-e200048

2020

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Less is More: Simultaneous View Classification and Landmark Detection for Abdominal Ultrasound Images

Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, p.711-719

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Complete valvular heart apparatus model from 4D cardiac CT

Medical image analysis, 2012-07, Vol.16 (5), p.1003-1014

2012

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Large-Scale Study on AI’s Impact on Identifying Chest Radiographs with No Actionable Disease in Outpatient Imaging

Academic radiology, 2024-07

2024

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Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019, p.676-684

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Learning to Recognize Abnormalities in Chest X-Rays with Location-Aware Dense Networks

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, p.757-765

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Probabilistic Sparse Matching for Robust 3D/3D Fusion in Minimally Invasive Surgery

IEEE transactions on medical imaging, 2015-01, Vol.34 (1), p.49-60

2015

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Automatic Liver Segmentation Using an Adversarial Image-to-Image Network

Machine learning automatically detects COVID-19 using chest CTs in a large multicenter cohort

AUCReshaping: improved sensitivity at high-specificity

A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation

Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings

Correction: A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation

Class-Aware Adversarial Lung Nodule Synthesis In CT Images

Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans

COSST: Multi-Organ Segmentation With Partially Labeled Datasets Using Comprehensive Supervisions and Self-Training

Towards intelligent robust detection of anatomical structures in incomplete volumetric data

No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting With Adversarial Attacks

3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes

Automated Detection and Quantification of COVID-19 Airspace Disease on Chest Radiographs: A Novel Approach Achieving Expert Radiologist-Level Performance Using a Deep Convolutional Neural Network Trained on Digital Reconstructed Radiographs From Computed Tomography-Derived Ground Truth

Quantifying and leveraging predictive uncertainty for medical image assessment

Semiautomatically Quantified Tumor Volume Using 68 Ga-PSMA-11 PET as a Biomarker for Survival in Patients with Advanced Prostate Cancer

Semiautomatically Quantified Tumor Volume Using 68Ga-PSMA-11 PET as a Biomarker for Survival in Patients with Advanced Prostate Cancer

Robust classification from noisy labels: Integrating additional knowledge for chest radiography abnormality assessment

Detection and characterization of COVID-19 findings in chest CT: Feasibility and applicability of an AI-based software tool

Automated Quantification of CT Patterns Associated with COVID-19 from Chest CT

Less is More: Simultaneous View Classification and Landmark Detection for Abdominal Ultrasound Images

Complete valvular heart apparatus model from 4D cardiac CT

Large-Scale Study on AI’s Impact on Identifying Chest Radiographs with No Actionable Disease in Outpatient Imaging

Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment

Learning to Recognize Abnormalities in Chest X-Rays with Location-Aware Dense Networks

Probabilistic Sparse Matching for Robust 3D/3D Fusion in Minimally Invasive Surgery

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