3.1k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National Institutes of HealthUS40 papers
- National Cancer InstituteUS8 papers
- Ping An (China)8 papers
- National Center for Biotechnology InformationUS7 papers
- Nvidia (United States)US7 papers
- University of PennsylvaniaUS5 papers
- Vanderbilt UniversityUS5 papers
- German Cancer Research CenterDE4 papers
- Heidelberg UniversityDE4 papers
- Imperial College LondonGB4 papers
- King's College LondonGB4 papers
- Radboud University Medical CenterNL4 papers
10 papers · 1 filter
3D Context Enhanced Region-based Convolutional Neural Network for End-to-End Lesion Detection
Ke Yan, Mohammadhadi Bagheri, Ronald M. Summers
Detecting lesions from computed tomography (CT) scans is an important but difficult problem because non-lesions and true lesions can appear similar. 3D context is known to be helpf…
Synthesizing CT from Ultrashort Echo-Time MR Images via Convolutional Neural Networks
Snehashis Roy, John A. Butman, Dzung L. Pham
With the increasing popularity of PET-MR scanners in clinical applications, synthesis of CT images from MR has been an important research topic. Accurate PET image reconstruction r…
Attention-Guided Curriculum Learning for Weakly Supervised Classification and Localization of Thoracic Diseases on Chest Radiographs
Yuxing Tang, Xiaosong Wang, Adam P. Harrison +3
In this work, we exploit the task of joint classification and weakly supervised localization of thoracic diseases from chest radiographs, with only image-level disease labels coupl…
CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement
Youbao Tang, Jinzheng Cai, Le Lu +5
Automated lesion segmentation from computed tomography (CT) is an important and challenging task in medical image analysis. While many advancements have been made, there is room fo…
Semi-Automatic RECIST Labeling on CT Scans with Cascaded Convolutional Neural Networks
Youbao Tang, Adam P. Harrison, Mohammadhadi Bagheri +2
Response evaluation criteria in solid tumors (RECIST) is the standard measurement for tumor extent to evaluate treatment responses in cancer patients. As such, RECIST annotations m…
Adversarial Image Registration with Application for MR and TRUS Image Fusion
Pingkun Yan, Sheng Xu, Ardeshir R. Rastinehad +1
Robust and accurate alignment of multimodal medical images is a very challenging task, which however is very useful for many clinical applications. For example, magnetic resonance…
White matter hyperintensity segmentation from T1 and FLAIR images using fully convolutional neural networks enhanced with residual connections
Dakai Jin, Ziyue Xu, Adam P. Harrison +1
Segmentation and quantification of white matter hyperintensities (WMHs) are of great importance in studying and understanding various neurological and geriatric disorders. Although…
DeepPap: Deep Convolutional Networks for Cervical Cell Classification
Ling Zhang, Le Lu, Isabella Nogues +3
Automation-assisted cervical screening via Pap smear or liquid-based cytology (LBC) is a highly effective cell imaging based cancer detection tool, where cells are partitioned into…
Convolutional Invasion and Expansion Networks for Tumor Growth Prediction
Ling Zhang, Le Lu, Ronald M. Summers +2
Tumor growth is associated with cell invasion and mass-effect, which are traditionally formulated by mathematical models, namely reaction-diffusion equations and biomechanics. Such…
Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection
Yuxing Tang, Josiah Wang, Xiaofang Wang +4
Deep CNN-based object detection systems have achieved remarkable success on several large-scale object detection benchmarks. However, training such detectors requires a large numbe…