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Taxonomy: IM- Cone Beam CT: Segmentation
| PO-GePV-M-323 | Auto-Segmentation for Limited Field of View CBCT in Male Pelvic Region Using Deep Learning Method H Hirashima1*, M Nakamura2, K Imanishi3, M Nakao4, T Mizowaki5, (1) Kyoto University, Graduate School of Medicine, Department of Radiation Oncology and Image-Applied Therapy, Kyoto, JP, (2) Kyoto University, Graduate School of Medicine, Department of Human Health Sciences, Kyoto, JP, (3) e-Growth Co., Ltd., Hyogo, JP, (4) Kyoto University, Graduate School of Informatics, Department of Systems Science, Kyoto, JP,(5) Kyoto University, Graduate School of Medicine, Department of Radiation Oncology and Image-Applied Therapy, Kyoto, JP |
| SU-F-201-3 | Leveraging the Elliptical Shape of the Uterocervix On Semi-Axial Cross-Sections for Improved Deep-Learning Segmentation On Cone-Beam CT S Mason1*, L Wang2, K Zormpas-Petridis2, M Blackledge2, S Lalondrelle1, H Mcnair1, E Harris2, (1) Royal Marsden NHS Foundation Trust, Sutton, SRY, GB, (2) Institute Of Cancer Research |
| WE-G-BRC-2 | Cascaded Learning-Based Cone Beam CT Head-And-Neck Multi-Organ Segmentation Y Lei, X Dai*, Z Tian, T Wang, J Zhou, J Roper, B Ghavidel, M McDonald, D Yu, J Bradley, T Liu, X Yang, Winship Cancer Institute of Emory University, Atlanta, GA |