Selected Publications

Journal Articles

European Radiology

The added value of an artificial intelligence system in assisting radiologists on indeterminate BI-RADS 0 mammograms

Chunyan Yi*, Yuxing Tang*, Yanbo Zhang, Rushan Ouyang, Zhenjie Cao, Zhicheng Yang, Shibin Wu, Mei Han, Jing Xiao, Peng Chang, Jie Ma (* co-first authors)

European Radiology, 2021.

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We found that our mammographic CAD system could assist mid-level radiologists in effectively reducing unnecessary BI-RADS 0 mammogram recalls and the benign biopsy rate without missing highly malignant tumors.
MedIA

MommiNet-v2: Mammographic multi-view mass identification networks

Zhicheng Yang, Zhenjie Cao, Yanbo Zhang, Yuxing Tang, Xiaohui Lin, Rushan Ouyang, Mingxiang Wu, Mei Han, Jing Xiao, Lingyun Huang, Shibin Wu, Peng Chang, Jie Ma

Medical Image Analysis (MedIA), 2021.

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MommiNet-v2 aggregates information from the high-resolution representations of all mammographic views and incorporates the malignancy information from both biopsy and BI-RADS categories.
MedIA

A disentangled generative model for disease decomposition in chest X-rays via normal image synthesis

Youbao Tang, Yuxing Tang, Yingying Zhu, Jing Xiao, Ronald M. Summers

Medical Image Analysis (MedIA), 2021.

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A novel disentangled generative deep model for chest X-ray decomposition that can interpret chest X-rays by outputting disease residue or saliency maps, to improve radiology workflow and patient care.
MedIA

Discriminative ensemble learning for few-shot chest x-ray diagnosis

Angshuman Paul, Yu-Xing Tang, Thomas C. Shen, Ronald M. Summers

Medical Image Analysis (MedIA), 2021.

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A two-step solution for few-shot learning for disease classification in chest X-rays.
TBD

COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature

Yifan Peng, Yu-Xing Tang, Sungwon Lee, Yingying Zhu, Ronald M. Summers, Zhiyong Lu

IEEE Transactions on Big Data (TBD), 2021.

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We develop a framework for rapidly constructing a chest X-ray/CT database containing Covid-19 images from PubMed Central® (PMC) full-text articles.
npj Digital Medicine

Automated abnormality classification of chest radiographs using deep convolutional neural networks

Yu-Xing Tang, You-Bao Tang, Yifan Peng, Ke Yan, Mohammadhadi Bagheri, Bernadette A. Redd, Catherine J. Brandon, Zhiyong Lu, Mei Han, Jing Xiao, Ronald M. Summers

npj Digital Medicine, Nature Publishing Group, 2020.

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AI algorithms can distinguish normal and abnormal chest X-rays with accuracy comparable to that of experienced radiologists, allowing these studies to be triaged for priority review.
TMI

Learning from multiple datasets with heterogeneous and partial labels for universal lesion detection in CT

Ke Yan, Jinzheng Cai, Youjing Zheng, Adam P. Harrison, Dakai Jin, Youbao Tang, Yuxing Tang, Lingyun Huang, Jing Xiao, Le Lu

IEEE Transactions on Medical Imaging (TMI), 2020.

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LENS (Lesion ENSemble) is a universal lesion detection framework that can effectively learn with multiple heterogeneous datasets and mine missing annotations from partially-labeled datasets.
TPAMI

Visual and semantic knowledge transfer for large scale semi-supervised object detection

Yuxing Tang, Josiah Wang, Xiaofang Wang, Boyang Gao, Emmanuel Dellandrea, Robert Gaizauskas, Liming Chen

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.

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Can knowledge about visual and semantic similarities of object categories help improve the performance of detectors trained in a semi- or weakly- supervised setting?
TMM

Weakly supervised learning of deformable part-based models for object detection via region proposals

Yuxing Tang, Xiaofang Wang, Emmanuel Dellandrea, Liming Chen

IEEE Transactions on Multimedia (TMM), 2017.

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Using region proposals to improve the weakly supervised deformable part-based model.
TIP

A global/local affinity graph for image segmentation

Xiaofang Wang, Yuxing Tang, Simon Masnou, Liming Chen

IEEE Transactions on Image Processing (TIP), 2015.

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A sparse global/local affinity graph over superpixels of an input image to capture both short and long range grouping cues.

Conference Proceedings

CVPR

Leveraging large-scale weakly labeled data for semi-supervised mass detection in mammograms

Yuxing Tang, Zhenjie Cao, Yanbo Zhang, Zhicheng Yang, Zongcheng Ji, Yiwei Wang, Mei Han, Jie Ma, Jing Xiao, Peng Chang

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

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A novel self-training framework for semi-supervised mass detection with soft image-level labels generated from diagnosis reports by a RoBERTa-based NLP model.
MICCAI

BI-RADS classification of calcification on mammograms

Yanbo Zhang, Yuxing Tang, Zhenjie Cao, Mei Han, Jing Xiao, Jie Ma, Peng Chang

International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.

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A deep learning-based BI-RADS classification for individual calcification in mammograms. A new evaluation metric for BI-RADS classification which considers the severity of malignancy.
MICCAI

Supervised contrastive pre-training for mammographic triage screening models

Zhenjie Cao, Zhicheng Yang, Yuxing Tang, Yanbo Zhang, Mei Han, Jing Xiao, Jie Ma, Peng Chang

International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.

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A framework of supervised contrastive pre-training followed by supervised fine-tuning to improve mammographic triage screening models.
MICCAI

E²Net: An edge enhanced network for accurate liver and tumor segmentation on CT scans

Youbao Tang, Yuxing Tang, Yingying Zhu, Jing Xiao, Ronald M. Summers

International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020.

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A two-stage framework (edge enhanced network) for 2D liver and tumor segmentation on CT scans.