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AI for Brain Lesion Detection and Trauma Video Action Recognition: First BONBID-HIE Lesion Segmentation Challenge and First Trauma Thompson Challenge, [Paperback]

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  • Category: Books (Computers)
  • ISBN-10:  3031716256
  • ISBN-10:  3031716256
  • ISBN-13:  9783031716256
  • ISBN-13:  9783031716256
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  100
  • Pages:  100
  • Binding:  Paperback
  • Binding:  Paperback
  • SKU:  3031716256-11-SPRI
  • SKU:  3031716256-11-SPRI
  • Item ID: 107058260
  • List Price: $129.99
  • Seller: ShopSpell
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  • Delivery by: Sep 29 to Oct 01
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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.

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