Topology- and Graph-Informed Imaging Informatics: First International Workshop, TGI3 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings | SpringerLink
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Topology- and Graph-Informed Imaging Informatics

First International Workshop, TGI3 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings

  • Conference proceedings
  • © 2025

Overview

Editors:
  1. Chao Chen

    1. Stony Brook University, Stony Brook, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Yash Singh

    1. Mayo Clinic, Rochester, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Xiaoling Hu

    1. Harvard University, Boston, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 15239)

Included in the following conference series:

Conference proceedings info: TGI3 2024.

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About this book

This book constitutes the proceedings of the First International Workshop on Topology- and Graph-Informed Imaging Informatics, TGI3 2024, held in conjunction with the 27th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco in October 2024.

The 13 full papers presented here were carefully reviewed and selected. These papers focus on the application of Topological Data Analysis (TDA) techniques, along with other computational techniques, for summarizing, analyzing, quantifying, and visualizing complex medical data for a more effective and efficient analysis.

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Table of contents (13 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Deep Learning-Based Liver Vessel Separation with Plug-and-Play Modules: Skeleton Tracking and Graph Attention

    • Chenhao Pei, Wei Wang, Huan Zhang, Siyuan Yin, Wen Tang, Ming Meng et al.
    Pages 1-10

  3. ccDice: A Topology-Aware Dice Score Based on Connected Components

    • Pierre Rougé, Odyssée Merveille, Nicolas Passat
    Pages 11-21

  4. TopOC: Topological Deep Learning for Ovarian and Breast Cancer Diagnosis

    • Saba Fatema, Brighton Nuwagira, Sayoni Chakraborty, Reyhan Gedik, Baris Coskunuzer
    Pages 22-32

  5. Analyzing Brain Tumor Connectomics Using Graphs and Persistent Homology

    • Debanjali Bhattacharya, Ninad Aithal, Manish Jayswal, Neelam Sinha
    Pages 33-42

  6. A Bispectral 3D U-Net for Rotation Robustness in Medical Segmentation

    • Arthur Chevalley, Valentin Oreiller, Julien Fageot, John O. Prior, Vincent Andrearczyk, Adrien Depeursinge
    Pages 43-54

  7. Restoring Connectivity in Vascular Segmentations Using a Learned Post-processing Model

    • Sophie Carneiro-Esteves, Antoine Vacavant, Odyssée Merveille
    Pages 55-65

  8. Multi-factor Component Tree Loss Function: A Topology-Preserving Method for Skeleton Segmentation from Bone Scintigrams

    • Anh Q. Nguyen, Jean Cousty, Yukiko Kenmochi, Shigeaki Higashiyama, Joji Kawabe, Akinobu Shimizu
    Pages 66-75

  9. Exploitation of Mapper Algorithm in Neuroimaging Applications: A Novel Framework for Outcomes Prediction

    • Stefano Vannoni, Emma Tassi, Inês Won Sampaio, Eleonora Maggioni
    Pages 76-87

  10. Topological Data Analysis of Resting-State fMRI Suggests Altered Brain Network Topology in Functional Dyspepsia: A Mapper-Based Parcellation Approach

    • Emma Tassi, Harrison Fisher, Andrew Bolender, Jun-Hwan Lee, Lizbeth J. Ayoub, Anna Maria Bianchi et al.
    Pages 88-99

  11. P-Count: Persistence-Based Counting of White Matter Hyperintensities in Brain MRI

    • Xiaoling Hu, Annabel Sorby-Adams, Frederik Barkhof, W. Taylor Kimberly, Oula Puonti, Juan Eugenio Iglesias
    Pages 100-110

  12. Outlier Detection in Large Radiological Datasets Using UMAP

    • Mohammad Tariqul Islam, Jason W. Fleischer
    Pages 111-121

  13. A Topological Comparison of the Fluorescence Imitating Brightfield Imaging and H&E Imaging

    • Meiliong Xu, Nate Anderson, Richard M. Levenson, Prateek Prasanna, Chao Chen
    Pages 122-133

  14. Topological Analysis of Seizure-Induced Changes in Brain Hierarchy Through Effective Connectivity

    • Anass B. El-Yaagoubi, Moo K. Chung, Hernando Ombao
    Pages 134-145

  15. Back Matter

    Pages 147-148
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Other volumes

  1. Topology- and Graph-Informed Imaging Informatics

Editors and Affiliations

  • Stony Brook University, Stony Brook, USA

    Chao Chen

  • Mayo Clinic, Rochester, USA

    Yash Singh

  • Harvard University, Boston, USA

    Xiaoling Hu

Bibliographic Information

  • Book Title: Topology- and Graph-Informed Imaging Informatics

  • Book Subtitle: First International Workshop, TGI3 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings

  • Editors: Chao Chen, Yash Singh, Xiaoling Hu

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-73967-5

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2025

  • Softcover ISBN: 978-3-031-73966-8Published: 11 October 2024

  • eBook ISBN: 978-3-031-73967-5Published: 10 October 2024

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: X, 148

  • Number of Illustrations: 4 b/w illustrations, 56 illustrations in colour

  • Topics: Computer Imaging, Vision, Pattern Recognition and Graphics, Analytical Chemistry, Biological Techniques

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