Daguang Xu

Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation

Jan 07, 2021
Vishwesh Nath, Dong Yang, Bennett A. Landman, Daguang Xu, Holger R. Roth

* IEEE Transactions on Medical Imaging, 2020
* 19 pages, 13 figures, Transactions of Medical Imaging

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Transformer Query-Target Knowledge Discovery (TEND): Drug Discovery from CORD-19

Dec 11, 2020
Leo K. Tam, Xiaosong Wang, Daguang Xu

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Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan

Nov 23, 2020
Dong Yang, Ziyue Xu, Wenqi Li, Andriy Myronenko, Holger R. Roth, Stephanie Harmon, Sheng Xu, Baris Turkbey, Evrim Turkbey, Xiaosong Wang, Wentao Zhu, Gianpaolo Carrafiello, Francesca Patella, Maurizio Cariati, Hirofumi Obinata, Hitoshi Mori, Kaku Tamura, Peng An, Bradford J. Wood, Daguang Xu

* Accepted with minor revision to Medical Image Analysis

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Learning Image Labels On-the-fly for Training Robust Classification Models

Oct 02, 2020
Xiaosong Wang, Ziyue Xu, Dong Yang, Leo Tam, Holger Roth, Daguang Xu

* v2: Minor Corrections

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Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning

Sep 28, 2020
Pochuan Wang, Chen Shen, Holger R. Roth, Dong Yang, Daguang Xu, Masahiro Oda, Kazunari Misawa, Po-Ting Chen, Kao-Lang Liu, Wei-Chih Liao, Weichung Wang, Kensaku Mori

* Accepted by MICCAI DCL Workshop 2020

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Democratizing Artificial Intelligence in Healthcare: A Study of Model Development Across Two Institutions Incorporating Transfer Learning

Sep 25, 2020
Vikash Gupta1, Holger Roth, Varun Buch3, Marcio A. B. C. Rockenbach, Richard D White, Dong Yang, Olga Laur, Brian Ghoshhajra, Ittai Dayan, Daguang Xu, Mona G. Flores, Barbaros Selnur Erdal

* 8 pages, 5 figures, pre-print

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Going to Extremes: Weakly Supervised Medical Image Segmentation

Sep 25, 2020
Holger R Roth, Dong Yang, Ziyue Xu, Xiaosong Wang, Daguang Xu

* 13 pages, 6 figures, 1 table

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Deep Hiearchical Multi-Label Classification Applied to Chest X-Ray Abnormality Taxonomies

Sep 23, 2020
Haomin Chen, Shun Miao, Daguang Xu, Gregory D. Hager, Adam P. Harrison

* MEDIMA 101811, 5 September 2020

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Federated Learning for Breast Density Classification: A Real-World Implementation

Sep 17, 2020
Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard White, Behrooz Hashemian, Thomas Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina V. Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel Rubin, Jayashree Kalpathy-Cramer

* Accepted at the 1st MICCAI Workshop on "Distributed And Collaborative Learning"; add citation to Fig. 1 & 2 and update Fig. 5

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Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies

Jul 31, 2020
Leo K. Tam, Xiaosong Wang, Evrim Turkbey, Kevin Lu, Yuhong Wen, Daguang Xu

* Accepted at Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2020

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Multi-Domain Image Completion for Random Missing Input Data

Jul 10, 2020
Liyue Shen, Wentao Zhu, Xiaosong Wang, Lei Xing, John M. Pauly, Baris Turkbey, Stephanie Anne Harmon, Thomas Hogue Sanford, Sherif Mehralivand, Peter Choyke, Bradford Wood, Daguang Xu

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

Jun 28, 2020
Yingda Xia, Dong Yang, Zhiding Yu, Fengze Liu, Jinzheng Cai, Lequan Yu, Zhuotun Zhu, Daguang Xu, Alan Yuille, Holger Roth

* Medical Image Analysis, 2020
* 19 pages, 6 figures, to appear in Medical Image Analysis. This article is an extension of the conference paper arXiv:1811.12506

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LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation

Jun 26, 2020
Wentao Zhu, Can Zhao, Wenqi Li, Holger Roth, Ziyue Xu, Daguang Xu

* MICCAI 2020 Early Accepted paper. Code is available\footnote{https://monai.io/research/lamp-automated-model-parallelism}

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Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation

Jun 10, 2020
Dong Yang, Holger Roth, Ziyue Xu, Fausto Milletari, Ling Zhang, Daguang Xu

* Published at MICCAI 2019
* 9 pages, 1 figures

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C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation

Dec 20, 2019
Qihang Yu, Dong Yang, Holger Roth, Yutong Bai, Yixiao Zhang, Alan L. Yuille, Daguang Xu

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End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation

Oct 15, 2019
Jinzheng Cai, Yingda Xia, Dong Yang, Daguang Xu, Lin Yang, Holger Roth

* Accepted to International Workshop on Machine Learning in Medical Imaging (MLMI2019)

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NeurReg: Neural Registration and Its Application to Image Segmentation

Oct 04, 2019
Wentao Zhu, Andriy Myronenko, Ziyue Xu, Wenqi Li, Holger Roth, Yufang Huang, Fausto Milletari, Daguang Xu

* WACV 2020 first round early accept; supplementary https://drive.google.com/file/d/1kzTLQn8cpoQNAYWUDJMtN5HcqhbWbl7G/view?usp=sharing; code will be released soon under NVIDIA open source; demos https://www.youtube.com/watch?v=GYLD7t7dSAg&t=3s

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Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network

Jul 08, 2019
Ziyue Xu, Xiaosong Wang, Hoo-Chang Shin, Dong Yang, Holger Roth, Fausto Milletari, Ling Zhang, Daguang Xu

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Neural Multi-Scale Self-Supervised Registration for Echocardiogram Dense Tracking

Jun 18, 2019
Wentao Zhu, Yufang Huang, Mani A Vannan, Shizhen Liu, Daguang Xu, Wei Fan, Zhen Qian, Xiaohui Xie

* Blood tracking video: https://youtu.be/pEA6ZmtTNuQ Muscle tracking video: https://youtu.be/NvLrCaqCiAE

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Daguang Xu

Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation

Transformer Query-Target Knowledge Discovery (TEND): Drug Discovery from CORD-19

Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan

Learning Image Labels On-the-fly for Training Robust Classification Models

Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning

Democratizing Artificial Intelligence in Healthcare: A Study of Model Development Across Two Institutions Incorporating Transfer Learning

Going to Extremes: Weakly Supervised Medical Image Segmentation

Deep Hiearchical Multi-Label Classification Applied to Chest X-Ray Abnormality Taxonomies

Federated Learning for Breast Density Classification: A Real-World Implementation

Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies

Multi-Domain Image Completion for Random Missing Input Data

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

LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation

Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation

Enhancing Foreground Boundaries for Medical Image Segmentation

The Future of Digital Health with Federated Learning

When Radiology Report Generation Meets Knowledge Graph

VerSe: A Vertebrae Labelling and Segmentation Benchmark

C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation

End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation

NeurReg: Neural Registration and Its Application to Image Segmentation

Cardiac Segmentation of LGE MRI with Noisy Labels

Weakly supervised segmentation from extreme points

Privacy-preserving Federated Brain Tumour Segmentation

Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network

Neural Multi-Scale Self-Supervised Registration for Echocardiogram Dense Tracking