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Taxonomy: IM/TH- Image Analysis (Single Modality or Multi-Modality): Computer-aided decision support systems (detection, diagnosis, risk prediction, staging, treatment response assessment/monitoring, prognosis prediction)

MO-EF-TRACK 4-4Imaging Based Prediction of Proliferative Foci as a Target for Surgical Intervention Across Glioma Grades
E Gates*, A Celaya, D Suki, J Weinberg, S Prabhu, D Fuentes, D Schellingerhout, University Of Texas MD Anderson Cancer Center, Houston, TX
PO-GePV-M-53Multi-Modality (PET/CT) Radiomics Based Recurrence Prediction in Head and Neck Cancers Prior to Radiotherapy
M Schelin*, R Sheu, R Bakst, J Junn, Y Yuan, The Mount Sinai Hospital, New York, NY
PO-GePV-M-237Interpretable Artificial Intelligence-Based Extracapsular Extension Prediction in Head and Neck Cancer Analysis
Y Wang1, W Duggar2*, T Thomas2, P Roberts2, R Gatewood2, L Bian1, H Wang1, (1) Mississippi State University, (2) University of Mississippi Med. Center
SU-E-TRACK 6-1A Multi-Modality Radiomics-Based Model for Recurrence Risk Stratification in Non-Small Cell Lung Cancer
J Christie1*, O Daher1, M Abdelrazek1, P Lang1, V Nair2, S Mattonen1, (1) Western University, London, ON, CA, (2) University of Washington School of Medicine, Seattle, WA
SU-E-TRACK 6-2Computer-Assisted Diagnosis of Hepatic Portal Hypertension: A Novel, Attention-Guided Deep Learning Framework Based On CT Imaging and Laboratory Data Integration
Y Wang*, X Li, M Konanur, B Konkel, E Seyferth, N Brajer, M Bashir, K Lafata, Duke University, Durham, NC
SU-E-TRACK 6-6A Radiomics-Boosted Deep Learning Model for COVID-19 and Non-COVID-19 Pneumonia Detection Using Chest X-Ray Image
Z Hu1*, Z Yang2, F Yin2, K Lafata2, C Wang2, (1) Duke Kunshan University, Kunshan, Jiangsu, China, (2) Duke University Medical Center, Durham, NC
TH-IePD-TRACK 3-3Attention Guided Network for Vestibular Schwannoma Growth Prediction
K Wang*, L Chen, N George-Jones, J Hunter, J Wang, UT Southwestern Medical Center, Dallas, TX
TU-IePD-TRACK 4-1A Clinically Implemented Watchdog Program to Streamline Adaptive LINAC-Based Head and Neck Radiotherapy
M Aristophanous*, E Aliotta, A Caringi, B Rochford, N Allgood, P Zhang, Y Hu, P Zhang, L Cervino, Memorial Sloan Kettering Cancer Center, New York, NY
WE-IePD-TRACK 2-5Predicting Breast Cancer Hormone Receptor Status with PET/MR Images Using Dual-Input Deep Convolutional Neural Network (DCNN)
S Choi1*, H Cho2, C Lee2, E Kong3, (1) Electronics and Telecommunications Research Institute (ETRI), Yuseong-gu, Daejeon, KR, (2) Korea Research Institute of Standards and Science (KRISS), Daejeon, KR, (2) Korea Research Institute of Standards and Science (KRISS), Daejeon, KR, (3) Yeungnam University Medical School And Hospital