AI for Brain Lesion Detection and Trauma Video Action Recognition: First BONBID-HIE Lesion Segmentation...

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Rina Bao Ellen Grant

AI for Brain Lesion Detection and Trauma Video Action Recognition

Name: AI for Brain Lesion Detection and Trauma Video Action Recognition
Price: 213.50 AUD
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ISBN: 9783031716256

First BONBID-HIE Lesion Segmentation Challenge and First Trauma Thompson Challenge, Held in...

Rina Bao, Ellen Grant, Andrew Kirkpatrick , Juan Wachs

$266.95 $213.50

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English

Springer International Publishing AG
24 November 2024

Artificial intelligence; Image processing

Series: Lecture Notes in Computer Science

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.

Edited by: Rina Bao, Ellen Grant, Andrew Kirkpatrick, Juan Wachs, Yangming Ou
Imprint: Springer International Publishing AG
Country of Publication: Switzerland
Edition: 2024 ed.
Volume: 14567
Dimensions: Height: 235mm, Width: 155mm,
ISBN: 9783031716256
ISBN 10: 3031716256
Series: Lecture Notes in Computer Science
Pages: 95
Publication Date: 24 November 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

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.