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Taxonomy: IM/TH- Image Analysis Skills (broad expertise across imaging modalities): Computer-aided decision support systems (detection, diagnosis, risk prediction, staging, treatment response assessment/monitoring, prognosis prediction)
| PO-GeP-I-79 | Developing a Novel Approach for ECG Classification Using Modified Local Binary Patterns e zeraatkar1*, M Gholamian2, N Jahani3, M Yazdi4, (1) Shiraz Urban Railway Organozation,Shiraz,IR (2) Shiraz University, Shiraz Iran,(3) Green Land Shiraz Eksir Chemical and Agricultural Industries Cimpant,Shiraz,Iran(4)Shiraz University,Shoraz Iran |
| PO-GeP-M-300 | MRI Radiomic Analysis for Survival Prediction in Diffuse Midline Glioma L Tam1, M Han1, D Yecies1, K Yeom1, S Mattonen2*, (1) Stanford University, Stanford, CA, USA (2) Western University, London, ON, CA |
| PO-GeP-M-329 | Predicting Prognosis of Posterior Fossa Ependymoma Using MRI Radiomics L Tam1, D Yecies1, M Han1, K Yeom1, S Mattonen2*, (1) Stanford University, Stanford, CA, USA (2) Western University, London, ON, CA |
| PO-GeP-M-331 | Predicting Treatment Outcome After Immunotherapy Based On Delta-Radiomic Model in Metastatic Melanoma X Chen1*, M Zhou1, K Wang2, Z Wang4, Z Zhou4, (1) Xi'an Jiaotong University, Xi'an, Shaanxi, CN, (2) UT Southwestern Medical Center, Dallas, TX, (3) Peking University Cancer Hospital, Beijing, CN, (4) University Of Central Missouri, Warrensburg, Missouri |
| PO-GeP-M-410 | Treatment of Oligoresistant and Oligoprogressive Disease in Metastatic Prostate Cancer Patients with Radiation Therapy A Roth1*, G Cooley1, J Smilowitz1, P Ferjancic1, G Liu1, R Jeraj1,2, (1) University of Wisconsin, Madison, WI, (2) University of Ljubljana, SI |
| PO-GeP-M-431 | Voxel Forecast Classifier to Predict Spatially Variant Binary Tumor Voxel Response On Longitudinal FDG-PET/CT Imaging of FLARE-RT Protocol Patients S Bowen1*, D Hippe1, W Chaovalitwongse2, P Thammasorn2, X Liu2, R Iranzad2, R Miyaoka1, H Vesselle1, P Kinahan1, R Rengan1, J Zeng1, (1) University of Washington, School of Medicine, Seattle, WA, (2) University of Arkansas, Fayetteville, AR |
| PO-GeP-T-409 | Evaluation of PET/clinical Parameters to Predict Toxicity in Chimeric Antigen Receptor T-Cell Therapy Patients with Relapsed/refractory Non-Hodgkin Lymphoma C Uche*, C Wright, J Baron, M Lariviere, A Barsky, D Miller, A Maity, J Plastaras, Y Xiao, University of Pennsylvania, Philadelphia, PA |
| SU-F-TRACK 1-7 | The Application of Partial Domain Adaptation Transfer Learning in the Classification of Retinopathy Using OCT Images From Different Datasets J Wu1*, D Li1, YM Yang2, (1) Shandong Normal University, Jinan, Shandong, CN, (2) UCLA, Los Angeles, CA |
| WE-D-TRACK 1-6 | Comparison of Automated Methods for Detection and Prognostication in Metastatic Prostate Cancer Using 18F-NaF PET/CT Images B Schott*1, A J Weisman1, T G Perk1, A R Roth1, S Yip2, G Liu1, R Jeraj13, (1) University of Wisconsin, Madison, WI, (2) AIQ Solutions, Madison, WI, (3) University of Ljubljana, Slovenia |
| WE-F-TRACK 1-4 | Deep-Learning for Differentiation of Benign From Malignant Parotid Lesions On MR Image B Feng1,2*, X Xia3, L Xu4, C Hu1,2, J Wang1,2, Z Zhang1,2, W Hu1,2, (1) Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, CN (2) Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, CN (3) Department of Radiology, Municipal Hospital Affiliated to Medical School of Taizhou University, Taizhou, CN (4) Department of Radiology, the Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, CN |
| WE-F-TRACK 1-5 | Prediction of Gleason Grade Group of Prostate Cancer On Multiparametric MRI Using Deep Learning, Transfer Learning, Representation Learning and Prototype Network W Zong*, M Pantelic, E Mohamed, N Wen, Henry Ford Health System, Detroit, MI |