Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic Vessel Tree from Multicenter Acquisition

Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic Vessel Tree from Multicenter Acquisition First Challenge, SEG.A. 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Pr

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Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic Vessel Tree from Multicenter Acquisition

Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic Vessel Tree from Multicenter Acquisition First Challenge, SEG.A. 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Pr

Sale price  $53.99 Regular price $59.99

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Lecture Notes in Computer Science

Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic Vessel Tree from Multicenter Acquisition

First Challenge, SEG.A. 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

Antonio Pepe | Gian Marco Melito | Jan Egger

Computers / Artificial Intelligence / Computer Vision & Pattern Recognition

This book constitutes the First Segmentation of the Aorta Challenge, SEG.A. 2023, which was held in conjunction with the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, on October 8, 2023. 

The 8 full and 3 short papers presented have been carefully reviewed and selected for inclusion in the book. They focus specifically on robustness, visual quality and meshing of automatically generated segmentations of aortic vessel trees from CT imaging. The challenge was organized as a ”container submission” challenge, where participants had to upload their algorithms to Grand Challenge in the form of Docker containers. Three tasks were created for SEG.A. 2023.



Publication Date: 10 February 2024
Publisher: Springer Nature Switzerland
Imprint: Springer
ISBN-13: 9783031532405
Format: Paperback softback
Page Count: 142

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