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

AvAntonio Pepe,Gian Marco Melito

Häftad, Engelska, 2024

Del 14539 i serien Lecture Notes in Computer Science

587 kr

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Beskrivning

This book constitutes the First Segmentation of the Aorta Challenge, SEG.A. 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.

Produktinformation

Utgivningsdatum:2024-02-10
Mått:155 x 235 x 9 mm
Vikt:248 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:142
Förlag:Springer International Publishing AG
ISBN:9783031532405

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Innehållsförteckning

M3F: Multi-Field-of-View Feature Fusion Network for Aortic Vessel Tree Segmentation in CT Angiography.- Aorta Segmentation from 3D CT in MICCAI SEG.A. 2023 Challenge.- A Data-Centric Approach for Segmenting the Aortic Vessel Tree: A Solution to SEG.A. Challenge 2023 Segmentation Task.- Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge.- Position-encoded pixel-to-prototype contrastive learning for aortic vessel tree segmentation.- Misclassification Loss for Segmentation of the Aortic Vessel Tree.- Deep Learning-based segmentation and mesh reconstruction of the Aortic Vessel Tree from CTA images.- RASNet: U-Net-based Robust Aortic Segmentation Network For Multicenter Datasets.- Optimizing Aortic Segmentation with an Innovative Quality Assessment: The Role of Global Sensitivity Analysis.- A mini tutorial on mesh generation of blood vessels for CFD applications.