Abstract is missing.
- M3F: Multi-Field-of-View Feature Fusion Network for Aortic Vessel Tree Segmentation in CT AngiographyYunsu Byeon, Hyeseong Kim, Kyungwon Kim, Doohyun Park, Euijoon Choi, Dosik Hwang. 1-12 [doi]
- Aorta Segmentation from 3D CT in MICCAI SEG.A. 2023 ChallengeAndriy Myronenko, Dong Yang 0005, Yufan He, Daguang Xu. 13-18 [doi]
- A Data-Centric Approach for Segmenting the Aortic Vessel Tree: A Solution to SEG.A. Challenge 2023 Segmentation TaskAyman El-Ghotni, Mohamed Nabil, Hossam El-Kady, Ahmed Ayyad, Amr Nasr. 19-41 [doi]
- Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A ChallengeMarek Wodzinski, Henning Müller. 42-54 [doi]
- Position-Encoded Pixel-to-Prototype Contrastive Learning for Aortic Vessel Tree SegmentationHyeongyu Kim, Yejee Shin, Dosik Hwang. 55-66 [doi]
- Misclassification Loss for Segmentation of the Aortic Vessel TreeAbbas Khan, Muhammad Asad 0001, Alexander M. Zolotarev, Caroline H. Roney, Anthony Mathur, Martin Benning, Gregory G. Slabaugh. 67-79 [doi]
- Deep Learning-Based Segmentation and Mesh Reconstruction of the Aortic Vessel Tree from CTA ImagesTheodoros P. Vagenas, Konstantinos Georgas, George K. Matsopoulos. 80-94 [doi]
- RASNet: U-Net-Based Robust Aortic Segmentation Network for Multicenter DatasetsJihan Zhang, Zhen Zhang, Liqin Huang. 95-109 [doi]
- Optimizing Aortic Segmentation with an Innovative Quality Assessment: The Role of Global Sensitivity AnalysisGian Marco Melito, Antonio Pepe 0003, Alireza Jafarinia, Thomas Krispel, Jan Egger. 110-126 [doi]
- A Mini Guide on Mesh Generation of Blood Vessels for CFD ApplicationsDomagoj Bosnjak, Thomas-Peter Fries. 127-134 [doi]
- Aortic Segmentations and Their Possible Clinical BenefitsChristian Mayer, Melanie Arnreiter, Barbara Karner, Sophie Hossain, Hannes Deutschmann, Daniel Zimpfer, Heinrich Mächler. 135-140 [doi]