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Taxonomy: IM/TH- Informatics: Informatics in Imaging (general)
| PO-GePV-I-4 | Design of a Display Test Pattern to Assess Ambient Light Levels in a Radiologists' Reading Environment C Guo1*, A Sanchez2, Z Lu1,3, E Marshall1,3, J Chung1, I Reiser1,3, (1) University Of Chicago Medical Center, Chicago, IL, (2) Vanderbilt University, Nashville, TN, (3) University of Chicago, Chicago, IL, |
| PO-GePV-M-18 | Using CNNs to Extract Standard Structure Names While Learning Radiomic Features W Sleeman*, P Bose, P Ghosh, J Palta, R Kapoor, Virginia Commonwealth University, Richmond, VA |
| PO-GePV-M-248 | A Medical Image Challenge Infrastructure K Farahani1*, J Kalpathy-Cramer2, B Bearce3, U Wagner4, (1) National Cancer Institute, Bethesda, MD, (2) Boston, MA, (3) No institution provided (4) Frederick National Lab, Frederick, MD |
| SU-E-TRACK 6-7 | Spatial Reconstruction of Statistically Significant Radiomics Signatures Using 3D Wavelet Decomposition in Tumors of Oropharyngeal Cancer H Bagher-Ebadian*, F Siddiqui, A Ghanem, S Zhu, M Lu, B Movsas, I Chetty, Henry Ford Health System, Detroit, MI |
| TH-EF-TRACK 8-0 | Imaging: Artificial Intelligence in Medical Imaging Y Liu1*, T Crawford2*, R Jones3*, B Nett4*, (1) Medical College of Wisconsin, Milwaukee, WI, (2) ,Milwaukee, WI, (3) Imagen Technologies, New York City, NY, (4) GE Healthcare Technologies, Waukesha, WI |
| TH-EF-TRACK 8-1 | Artificial intelligence in Medical Imaging Y Liu1*, T Crawford2*, R Jones3*, B Nett4*, (1) Medical College of Wisconsin, Milwaukee, WI, (2) ,Milwaukee, WI, (3) Imagen Technologies, New York City, NY, (4) GE Healthcare Technologies, Waukesha, WI |
| TH-EF-TRACK 8-2 | Artificial intelligence in Medical Imaging Y Liu1*, T Crawford2*, R Jones3*, B Nett4*, (1) Medical College of Wisconsin, Milwaukee, WI, (2) ,Milwaukee, WI, (3) Imagen Technologies, New York City, NY, (4) GE Healthcare Technologies, Waukesha, WI |
| TH-EF-TRACK 8-3 | Deep-Learning Systems for Fracture Detection in Musculoskeletal Radiographs Y Liu1*, T Crawford2*, R Jones3*, B Nett4*, (1) Medical College of Wisconsin, Milwaukee, WI, (2) ,Milwaukee, WI, (3) Imagen Technologies, New York City, NY, (4) GE Healthcare Technologies, Waukesha, WI |
| TH-EF-TRACK 8-4 | Deep Learning Image Reconstruction for CT: Principles, Performance and Clinical Applications Y Liu1*, T Crawford2*, R Jones3*, B Nett4*, (1) Medical College of Wisconsin, Milwaukee, WI, (2) ,Milwaukee, WI, (3) Imagen Technologies, New York City, NY, (4) GE Healthcare Technologies, Waukesha, WI |
| TH-EF-TRACK 8-5 | Q&A Y Liu1*, T Crawford2*, R Jones3*, B Nett4*, (1) Medical College of Wisconsin, Milwaukee, WI, (2) ,Milwaukee, WI, (3) Imagen Technologies, New York City, NY, (4) GE Healthcare Technologies, Waukesha, WI |
| TU-IePD-TRACK 4-4 | NCI Imaging Data Commons A Fedorov1*, W Longabaugh2, D Pot3, D Clunie4, S Pieper5, R Lewis6, H Aerts7, A Homeyer8, M Herrmann9, U Wagner10, T Pihl11, K Farahani12, R Kikinis13, (1) Brigham & Woman's Hospital, Boston, MA, (2) Institute for Systems Biology, Seattle, WA, (3) General Dynamics IT, Bethesda, MD, (4) PixelMed Publishing, Bangor, PA, (5) Isomics Inc., Cambridge, MA, (6) Radical Imaging, Boston, MA, (7) Dana-Farber/Brigham Womens Cancer Center, Boston, MA, (8) Fraunhofer MEVIS, Bremen, ,DE, (9) Massachusetts General Hospital, Boston, MA, (10) Frederick National Lab, Frederick, MD, (11) Frederick National Lab, Frederick, MD, (12) National Cancer Institute, Bethesda, MD, (13) Harvard Medical School, Boston, MA |