Baxter / Rekik / Eagleson Ethical and Philosophical Issues in Medical Imaging, Multimodal Learning and Fusion Across Scales for Clinical Decision Support, and Topological Data Analysis for Biomedical Imaging

1st International Workshop, EPIMI 2022, 12th International Workshop, ML-CDS 2022, 2nd International Workshop, TDA4BiomedicalImaging, Held in Conjunction with MICCAI 2022, Singapore, September 18–22, 2022, Proceedings
1. Auflage 2022
ISBN: 978-3-031-23223-7
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 135 Seiten

Reihe: Lecture Notes in Computer Science

This book constitutes the refereed joint proceedings of the 1 International Workshop on Ethical & Philosophical Issues in Medical Imaging (EPIMI 2022); the 12 International Workshop on Multimodal Learning and Fusion Across Scales for Clinical Decision Support (ML-CDS 2022) and the 2 International Workshop on Topological Data Analysis for Biomedical Imaging (TDA4BiomedicalImaging 2022), held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022, in Singapore, in September 2022.

EPIMI includes five short papers about various humanistic aspects of medical image computing and computer-assisted interventions. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The TDA papers focus on Topological Data Analysis: a collection of techniques and tools that have matured from an increasing interest in the role topologyplays in machine learning and data science.

Zielgruppe

Research

Autoren/Hrsg.

Baxter, John S. H.

Rekik, Islem

Eagleson, Roy

Zhou, Luping

Syeda-Mahmood, Tanveer

Wang, Hongzhi

Hajij, Mustafa

Inhaltsverzeichnis

Ethical and Philosophical Issues in Medical Imaging.- Data Poisoning Attack and Defenses in Connectome-based Predictive Models.- Disproportionate Subgroup Impacts and Other Challenges of Fairness in Artificial Intelligence for Medical Image Analysis.- Separable vs. End-to-End Learning: A critical examination of learning paradigms.- A 35-Year Longitudinal Analysis of Dermatology Patient Behavior across Economic and Cultural Manifestations in Tunisia, and the Impact of Digital Tools.- User-centered design for surgical innovations: A ventriculostomy case study.- Multimodal Learning and Fusion Across Scales for Clinical Decision Support.- Visually Aware Metadata-guided Supervision for Improved Skin Lesion Classification using Deep Learning.- Predicting Osteoarthritis of the Temporomandibular Joint Using Random Forest with Privileged Information.- Hybrid Network Based on Cross-modal Feature Fusion for Diagnosis of Alzheimer's Disease.- Topological Data Analysis for Biomedical Imaging.- Future Unruptured Intracranial Aneurysm Growth Prediction using Mesh Convolutional Neural Networks.- TDA-Clustering Strategies for the Characterization of Brain Organoids.- Fetal Cortex Segmentation with Topology and Thickness Loss Constraints.