Automated Contouring of Contrast and Noncontrast Computed Tomography Liver Images With Fully Convolutional Networks is a research paper published in Advances in Radiation Oncology (2020). On theSindex it has a DataRank of 0. It has been cited 30 times.
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National Institutes of Health
Grant: 1R01CA221971
National Institutes of Health
Grant: R01CA235564
National Institutes of Health
Grant: U01CA196403
National Institutes of Health
Grant: U54CA143837
NCI NIH HHS
Grant: R01 CA221971
National Institutes of Health
Grant: 5U01CA196403-05
Imaging and Molecular Correlates of Progression in Cystic Neoplasms of the Pancreas
National Institutes of Health
Grant: 5R01CA235564-05
Anatomical Modeling to Improve the Precision of Image Guided Liver Ablation
National Institutes of Health
Grant: 5U54CA143837-07
Multi-Scale Bio-Simulations
National Institutes of Health
Grant: 5R01CA221971-02
Optimization and Evaluation of Anatomical Models of Liver Radiation Response
Ipsen Biopharmaceuticals
Pancreatic Cancer Action Network
University of Texas MD Anderson Cancer Center
Society of Interventional Radiology
Data Science Institute, Columbia University
National Cancer Institute
Siemens Medical Solutions USA
American College of Radiology
University of Texas at Austin
FWCI
1.83
Citation Percentile
0.9%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals