Multi-class Segmentation of the Aorta

AortaSeg 2024 Challenge, Held in Conjunction with MICCAI 2024, Virtual Event, October 24, 2024, Proceedings

AvMuhammad Imran,Jonathan R. Krebs

Häftad, Engelska, 2026

Del 16399 i serien Lecture Notes in Computer Science

571 kr

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Beskrivning

This book constitutes the proceedings of the First MICCAI Challenge Multi-class Segmentation of the Aorta, AortaSeg 2024, held in conjunction with MICCAI 2024, as a virtual event, during October 2024. The 10 papers included in the book were carefully reviewed and selected from 16 submitting teams. This challenge aimed to advance the field of medical image segmentation by introducing the first large-scale, publicly available dataset for multi-class segmentation of the aorta, its branches, and clinically relevant zones in computed tomography angiography (CTA).

Produktinformation

Utgivningsdatum:2026-01-28
Mått:155 x 235 x 8 mm
Vikt:219 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:123
Förlag:Springer Nature Switzerland AG
ISBN:9783032142450

Utforska kategorier

Innehållsförteckning

.- Multi-Class Segmentation of Aortic Branches and Zones in CTA.- Coarse-to-Fine Aortic Segmentation on CTA Using a Two-Stage nnUNet-Based Framework..- Hierarchical Semantic Learning for Multi-Class Aorta Segmentation..- U-Net-Based Segmentation of Aortic Branches and Zones in CTA Scans..- Anatomically Guided Two-Stage 3D Aorta Segmentation in CT Angiography..- Combining Region-Based and Topological Losses in the nnU-Net Framework for Advanced Aorta Segmentation..- Data-Centric Multiclass Aortic Segmentation: Revisiting Classical Architectures in Low-Data Regimes..- AortaST: A Student-Teacher Framework for Multi-Class Aortic Segmentation..- Accurate and Efficient Multi-Class Segmentation for Aortic Branches and Zones in CTA..- Application of nnUNet for Multi-Class Segmentation of Aortic Branches and Zones in CTA..- A Mamba-Based Method with Gated Attention for Human Aorta Segmentation.

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