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Fast, Low-resource, and Accurate Organ and Pan-cancer Segmentation in Abdomen CT : MICCAI Challenge, FLARE 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings / / edited by Jun Ma, Bo Wang



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Titolo: Fast, Low-resource, and Accurate Organ and Pan-cancer Segmentation in Abdomen CT : MICCAI Challenge, FLARE 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings / / edited by Jun Ma, Bo Wang Visualizza cluster
Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Edizione: 1st ed. 2024.
Descrizione fisica: 1 online resource (373 pages)
Disciplina: 610.28563
Soggetto topico: Image processing - Digital techniques
Computer vision
Artificial intelligence
Computer networks
Application software
Education - Data processing
Software engineering
Computer Imaging, Vision, Pattern Recognition and Graphics
Artificial Intelligence
Computer Communication Networks
Computer and Information Systems Applications
Computers and Education
Software Engineering
Persona (resp. second.): MaJun
WangBo
Nota di bibliografia: Includes bibliographical references and index.
Sommario/riassunto: This book constitutes the proceedings of the MICCAI 2023 Challenge, FLARE 2023, held in Conjunction with MICCAI 2023, in Vancouver, BC, Canada, on October 8, 2023. The 27 full papers presented in this book were carefully reviewed and selected from 37 submissions. The papers present research and results for abdominal organ segmentation which has many important clinical applications, such as organ quantification, surgical planning, and disease diagnosis.
Titolo autorizzato: Fast, Low-resource, and Accurate Organ and Pan-cancer Segmentation in Abdomen CT  Visualizza cluster
ISBN: 3-031-58776-6
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910869182503321
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Serie: Lecture Notes in Computer Science, . 1611-3349 ; ; 14544