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AI for Brain Lesion Detection and Trauma Video Action Recognition -

AI for Brain Lesion Detection and Trauma Video Action Recognition

First BONBID-HIE Lesion Segmentation Challenge and First Trauma Thompson Challenge, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 16 and 12, 2023, Proceedings
Buch | Softcover
XIV, 95 Seiten
2024
Springer International Publishing (Verlag)
978-3-031-71625-6 (ISBN)
CHF 164,75 inkl. MwSt
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This book constitutes the proceedings of the First BONBID-HIE Lesion Segmentation Challenge and the First Trauma Thompson Challenge, held in conjunction with MICCAI 2023, in Vancouver, BC, Canada, during October 2023. 

For BONBID-HIE 2023 Challenge 6 papers have been accepted out of 14 submissions. They span a broad array of approaches leveraging anatomical information about HIE, data augmentation, training strategies, model architecture, and integration with traditional machine learning methods. For the TTC 2023 Trauma Thompson Challenge 4 accepted contributions are included in this book. They deal with advancements in machine learning methods and their practical applications in addressing small and diffuse lesions in HIE segmentation. 

BONBID-HIE 2023.- Fusion of Deep and Local Features Using Random Forests for Neonatal HIE Segmentation.- Enhancing Lesion Segmentation in the BONBID-HIE Challenge: An Ensemble Strategy.- An Ensemble Approach for Segmentation of Neonatal HIE lesions.- Improving Segmentation of Hypoxic Ischemic Encephalopathy Lesions by Heavy Data Augmentation: Contribution to the BONBID Challenge.- A Deep Neural Network Approach for the Lesion Segmentation from Neonatal Brain Magnetic Resonance Imaging.- SegResNet based Reciprocal Transformation for BONBID-HIE Lesion Segmentation.- Trauma THOMPSON 2023.- Overview of the Trauma THOMPSON Challenge at MICCAI 2023.- The Trauma THOMPSON Challenge Report MICCAI 2023.- Action Recognition and Action Anticipation Tasks in the Trauma THOMPSON Challenge Technical Report.- QuIIL at T3 challenge: Towards Automation in Life-Saving Intervention Procedures from First-Person View.

Erscheinungsdatum
Reihe/Serie Lecture Notes in Computer Science
Zusatzinfo XIV, 95 p. 29 illus., 27 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Action anticipation • Action Recognition • Artificial Intelligence • Brain Injury • brain MRI • Combat Casualty Care • Deep learning • Egocentric datasets • hypoxic ischemic encephalopathy • Image Segmentation • lesion segmentation • Life-saving interventions • machine learning • Medical image segmentation • Neonatal Brain Injury • surgical simulation • Visual Question Answering
ISBN-10 3-031-71625-6 / 3031716256
ISBN-13 978-3-031-71625-6 / 9783031716256
Zustand Neuware
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