AI for Brain Lesion Detection and Trauma Video Action Recognition
Springer International Publishing (Verlag)
978-3-031-71625-6 (ISBN)
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 | 25.10.2024 |
|---|---|
| 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 |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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