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Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation -

Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation

MICCAI Challenge, FLARE 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings

Jun Ma, Bo Wang (Herausgeber)

Buch | Softcover
XI, 270 Seiten
2025
Springer International Publishing (Verlag)
978-3-031-96201-1 (ISBN)
CHF 98,85 inkl. MwSt

This book constitutes the proceedings of the MICCAI 2024 Challenge, FLARE 2024, held in Conjunction with MICCAI 2024, in Marrakesh, Morocco, during October 2024. 

The 20 full papers included in this book were carefully reviewed and selected from 24 submissions. They describe the solutions the participants found for automatic abdominal organ and pan-cancer segmentation using the official training dataset released for this pupose.

This challenge focuses on both organ and pan-cancer segmentation, including three subtasks:

Subtask 1: Pan-cancer segmentation in CT scans
Subtask 2: Abdominal CT organ segmentation on laptop
Subtask 3: Unsupervised domain adaptation for abdominal organ segmentation in MRI Scans

Erscheinungsdatum
Reihe/Serie Lecture Notes in Computer Science
Zusatzinfo XI, 270 p. 73 illus., 70 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Schlagworte Abdomen • Artificial Intelligence • Computed tomography • computer vision • computer vision tasks • Computing Methodologies • machine learning • Medical image segmentation • Organ • Scene Understanding
ISBN-10 3-031-96201-X / 303196201X
ISBN-13 978-3-031-96201-1 / 9783031962011
Zustand Neuware
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Buch | Hardcover (2025)
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