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| MO-J430-CAMPUS-F1-3 | Machine Learning of Tumor Cluster Dosi-Radiomics to Predict Regional Changes On Early-Response FDG PET/CT Imaging of FLARE-RT Protocol Patients C Duan1,2,4 , W Chaovalitwongse2 , K Puk3 , P Thammasorn2 , S Wang3 , D Hippe4 , L Pierce4 , X Liu2 , J You1 , R Miyaoka4 , H Vesselle4 , P Kinahan4 , R Rengan4 , J Zeng4 , S Bowen4*, (1) Tongji University School of Economics & Management, Yangpu District, Shanghai, (2) University of Arkansas, Fayetteville, AR, (3) University of Texas, Austin, TX, (4) University of Washington School of Medicine, Seattle, WA |
| SU-F-DBRB-1 | Effects of Variability in Radiomics Software Packages in Classifying Patients with Radiation Pneumonitis J Foy*, J Fuhrman , S Armato , H Al-Hallaq , The University of Chicago, Chicago, IL |
| SU-H330-GePD-F6-3 | CT-Based Radiomics Predict Platinum-Sensitivity Status in Limited-Stage Small Cell Lung Cancer Patients Treated with Chemoradiotherapy Q Wen*, J Zhu , X Meng , T Bai , Y Yin , J Yu , Shandong Cancer Hospital Affliated to Shandong University, Shandong University,Jinan,China |
| SU-H330-GePD-F6-6 | Cone-Beam CT Radiomics Features as Potential Predictors for Esophageal Cancer Response J Teruel*, K Du , P Galavis , NYU Langone Health, New York, NY |
| SU-H330-GePD-F8-5 | Towards Quantitative Imaging: Mitigation of Dose-Influenced Variation in CT Quantitative Measures Using Bilateral Filtering Denoising M Wahi-Anwar*, N Emaminejad , J Hoffman , G Kim , M Brown , M McNitt-Gray , David Geffen School of Medicine at UCLA, Los Angeles, CA |
| SU-I-GPD-I-6 | Impact of Image Pre-Processing On Radiomics Feature Prediction Power in Recurrence Glioblastoma Patients G Hajianfar1*, I Shiri2 ,M Oveisi3 , H Maleki4 , A Haghparast1 , (1) Kermanshah University of Medical Sciences,Kermanshah,Iran, (2)(3)(4) Rajaie Cardiovascular Medical and Research Center, Tehran,Iran |
| SU-I-GPD-J-54 | Efficient Multi-GPU Calculation of Local Radiomic Features From 2D and 3D Images R Neph*, K Sheng , UCLA Dept. of Radiation Oncology, Los Angeles, CA |
| SU-K-205-6 | Radiomics Characteristics Correlate with Immune Activation: A TCIA/TCGA Data Analysis in Head and Neck Squamous Cell Carcinoma J Oh1*, E Katsoulakis1 , J Leeman1 , Y Yu2 , J Tsai1 , S McBride1 , N Katabi1 , A Apte1 , N Lee1 , V Hatzoglou1 , N Riaz1 , J Deasy1 , (1) Memorial Sloan Kettering Cancer Center, New York, NY, (2) University of California San Francisco, San Francisco, CA |
| TH-AB-DBRB-1 | Optimal Energy of Virtual Monoenergetic Imaging From Dual-Energy CT for Target Delineation and Radiation Response Assessment G Noid1*, D Schott1 , T Schmidt2 , A Tai1 , X Li1 , (1) Medical College of Wisconsin, Milwaukee, WI, (2) Marquette University, Milwaukee, WI, |
| TH-AB-DBRB-7 | Investigating the Complementarity of Radiomics and Clinical Information for Predicting Treatment Failure in Multiple Cancer Types M Vallieres1*, A Chatterjee2 , F Lucia3 , V Bourbonne3 , P Bonaffini4 , I Masson5 , A Mervoyer5 , C Reinhold4 , D Visvikis1 , U Schick3 , J Seuntjens2 , O Morin6 , M Hatt1 (1) Laboratoire de Traitement de l'Information Medicale (LaTIM, INSERM UMR 1101), Brest, France; (2) Medical Physics Unit, McGill University, Montreal, Quebec, Canada; (3) Radiation Oncology Department, CHRU Morvan Brest, Brest, France; (4) Radiology Department, McGill University Health Centre, Montreal, Quebec, Canada; (5) Radiation Oncology Department, Institut de Cancerologie de l'Ouest, Nantes, France; (6) Department of Radiation Oncology, Division of Physics, University of California San Francisco, San Francisco, CA, USA |
| TH-AB-KDBRC-3 | Automatic Contour Correction Based On Image Texture for MRI-Guided Online Adaptive Replanning Y Zhang*, D Schott , E Ahunbay , X Li , Froedtert Hospital and the Medical College of Wisconsin, Milwaukee, WI |
| TH-AB-KDBRC-4 | Image Texture Based Fast Contour Validation for Online Adaptive Radiation Replanning Y Zhang1*, Y Hao2 , C Kinchen1 , S Lim1 , X Li3 , (1) Medical College of Wisconsin, Milwaukee, WI, (2) Washington University School of Medicine, St. Louis, MO, (3) Froedtert Hospital and the Medical College of Wisconsin, Milwaukee, WI |
| TU-D-DBRB-6 | Robustness of Lung Nodule Classification by Radiomic Texture Feature Across CT Acquisition and Reconstruction Parameters N Emaminejad*, J Hoffman , M Wahi-Anwar , G Kim , M Brown , M McNitt-Gray , David Geffen School of Medicine at UCLA, Los Angeles, CA |
| WE-AB-KDBRC-4 | Clinical Validation of Four-Dimensional Computed Tomography-Based Lung Ventilation Images Using Texture Feature Analysis and Pulmonary Function Test H Zhang1*, M Huang2 , S Feigenberg2 , A Berman2 , W Lu3 , V Jain2 , Y Xiao2 , P Jin2 , P Mohindra1 , C Simone1 , S Bentzen1 , W D'Souza1 , (1) University of Maryland School of Medicine, Baltimore, MD, (2) University of Pennsylvania, Philadelphia, PA, (3) Memorial Sloan Kettering Cancer Center, New York, NY, |