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 / edited by Rina Bao, Ellen Grant, Andrew Kirkpatrick, Juan Wachs, Yangming Ou.

Format:

Book

Author/Creator:

Bao, Rina.

Contributor:

Grant, Ellen.

Kirkpatrick, Andrew.

Wachs, Juan.

Ou, Yangming.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 14567

Language:

English

Subjects (All):

Image processing--Digital techniques.

Image processing.

Computer vision.

Artificial intelligence.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Artificial Intelligence.

Local Subjects:

Computer Imaging, Vision, Pattern Recognition and Graphics.

Artificial Intelligence.

Physical Description:

1 online resource (106 pages)

Edition:

1st ed. 2025.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2025.

Summary:

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. .

Contents:

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.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

3-031-71626-4

OCLC:

1465267139