| Monday
8:30 AM | MO-B-BRC-1 : Clinical Applicability-Oriented Contour Quality Classification for Auto-Segmentation
Y. Zhang*, J. Ding, A. Amjad, C. Sarosiek, N. Dang, W. Hall, B. Erickson, X. Li |
| Monday
8:40 AM | MO-B-BRC-2 : Comprehensive Evaluation of a Real-Time 3D MR Imaging Technique Using a Deformation-Driven Deep Convolutional Neural Network (KS-RegNet)
H. Shao*, T. Li, M. Dohopolski, J. Wang, J. Cai, J. Tan, K. Wang, Y. Zhang |
| Monday
8:50 AM | MO-B-BRC-3 : Deep Learning-Guided Iterative Refinement to Improve Label Quality and Consistency
H. Zhou*, J. Xiao, Z. Fan, D. Ruan |
| Monday
9:00 AM | MO-B-BRC-4 : Patient-Specific Transfer Learning to Enhance the Performance of Deep Learning Auto-Segmentation in 0.35 T MRgRT for Prostate Cancer
M. Kawula*, I. Hadi, L. Nierer, M. Vagni, D. Cusumano, L. Boldrini, L. Placidi, S. Corradini, C. Belka, G. Landry, C. Kurz |
| Monday
9:10 AM | MO-B-BRC-5 : Quality Assurance of Head & Neck OARs Segmentation with Machine Learning and Deep Learning
J. Duan*, J. Castle, X. Feng, Q. Chen |
| Monday
9:20 AM | MO-B-BRC-6 : Twin AI Algorithms for Quality Control of Auto-Segmentation in Radiation Therapy
C. Guthier*, R. Zeleznik, D. Bitterman, R. Punglia, J. Bredfeldt, H. Aerts, R. Mak |
