Fast, Low-resource, and Accurate Organ and Pan-cancer Segmentation in Abdomen CT [electronic resource] : MICCAI Challenge, FLARE 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings / edited by Jun Ma, Bo Wang.
Contributor(s): Ma, Jun [editor.] | Wang, Bo [editor.] | SpringerLink (Online service).
Material type: BookSeries: Lecture Notes in Computer Science: 14544Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024.Description: XI, 364 p. 98 illus., 95 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031587764.Subject(s): 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 EngineeringAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006 Online resources: Click here to access online In: Springer Nature eBookSummary: 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.No physical items for this record
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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