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Record Nr. |
UNINA9910869182503321 |
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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 |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (373 pages) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 14544 |
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Disciplina |
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Soggetti |
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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 |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Sommario/riassunto |
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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. |
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