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Lieferstatus:	i.d.R. innert 7-14 Tagen versandfertig
Veröffentlichung:	Januar 2026
Genre:	EDV / Informatik
	AORTA / Artificial Intelligence / Computational Science and Engineering / Computed Tomography / Computer Imaging, Vision, Pattern Recognition and Graphics / Computer Vision / Computer vision tasks / Computing methodologies / machine learning / Maschinelles Lernen / Maschinelles Sehen, Bildverstehen / Medical Image Segmentation / Numerische Mathematik / scene understanding mehr...
ISBN:	9783032142450
EAN-Code:	9783032142450
Verlag:	Springer International Publishing
Einband:	Kartoniert
Sprache:	English
Dimensionen:	H 235 mm / B 155 mm / D
Seiten:	123
Illustration:	X, 123 p. 34 illus., 32 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

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).