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Uncertainty for Safe Utilization of Machine Learning in Medical Imaging

5th International Workshop, UNSURE 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Carole H. Sudre

    1. University College London, London, UK

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  2. Christian F. Baumgartner

    1. University of Tübingen, Tübingen, Germany

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  3. Adrian Dalca

    1. Harvard Medical School, Charlestown, USA

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  4. Raghav Mehta

    1. McGill University, Montreal, Canada

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  5. Chen Qin

    1. Imperial College London, London, UK

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  6. William M. Wells

    1. Department of Radiology, Brigham and Women’s Hospital, Boston, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14291)

Included in the following conference series:

Conference proceedings info: UNSURE 2023.

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Table of contents (21 papers)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Propagation and Attribution of Uncertainty in Medical Imaging Pipelines

    • Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert et al.
    Pages 1-11

  3. RR-CP: Reliable-Region-Based Conformal Prediction for Trustworthy Medical Image Classification

    • Yizhe Zhang, Shuo Wang, Yejia Zhang, Danny Z. Chen
    Pages 12-21

  4. Bayesian Uncertainty Estimation in Landmark Localization Using Convolutional Gaussian Processes

    • Lawrence Schobs, Thomas M. McDonald, Haiping Lu
    Pages 22-31

  5. TriadNet: Sampling-Free Predictive Intervals for Lesional Volume in 3D Brain MR Images

    • Benjamin Lambert, Florence Forbes, Senan Doyle, Michel Dojat
    Pages 32-41

  6. Examining the Effects of Slice Thickness on the Reproducibility of CT Radiomics for Patients with Colorectal Liver Metastases

    • Jacob J. Peoples, Mohammad Hamghalam, Imani James, Maida Wasim, Natalie Gangai, HyunSeon Christine Kang et al.
    Pages 42-52

  7. Benchmarking Scalable Epistemic Uncertainty Quantification in Organ Segmentation

    • Jadie Adams, Shireen Y. Elhabian
    Pages 53-63

  8. Numerical Uncertainty of Convolutional Neural Networks Inference for Structural Brain MRI Analysis

    • Inés Gonzalez Pepe, Vinuyan Sivakolunthu, Hae Lang Park, Yohan Chatelain, Tristan Glatard
    Pages 64-73

  9. How Inter-rater Variability Relates to Aleatoric and Epistemic Uncertainty: A Case Study with Deep Learning-Based Paraspinal Muscle Segmentation

    • Parinaz Roshanzamir, Hassan Rivaz, Joshua Ahn, Hamza Mirza, Neda Naghdi, Meagan Anstruther et al.
    Pages 74-83

  10. Uncertainty Estimation and Propagation in Accelerated MRI Reconstruction

    • Paul Fischer, K. Thomas, Christian F. Baumgartner
    Pages 84-94

  11. Uncertainty-Based Quality Assurance of Carotid Artery Wall Segmentation in Black-Blood MRI

    • Elina Thibeau-Sutre, Dieuwertje Alblas, Sophie Buurman, Christoph Brune, Jelmer M. Wolterink
    Pages 95-103

  12. Multi-layer Aggregation as a Key to Feature-Based OOD Detection

    • Benjamin Lambert, Florence Forbes, Senan Doyle, Michel Dojat
    Pages 104-114

  13. Feature-Based Pipeline for Improving Unsupervised Anomaly Segmentation on Medical Images

    • Daria Frolova, Aleksandr Katrutsa, Ivan Oseledets
    Pages 115-125

  14. Redesigning Out-of-Distribution Detection on 3D Medical Images

    • Anton Vasiliuk, Daria Frolova, Mikhail Belyaev, Boris Shirokikh
    Pages 126-135

  15. On the Use of Mahalanobis Distance for Out-of-distribution Detection with Neural Networks for Medical Imaging

    • Harry Anthony, Konstantinos Kamnitsas
    Pages 136-146

  16. Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image Segmentation

    • McKell Woodland, Nihil Patel, Mais Al Taie, Joshua P. Yung, Tucker J. Netherton, Ankit B. Patel et al.
    Pages 147-156

  17. Breaking Down Covariate Shift on Pneumothorax Chest X-Ray Classification

    • Bogdan Bercean, Alexandru Buburuzan, Andreea Birhala, Cristian Avramescu, Andrei Tenescu, Marius Marcu
    Pages 157-166

  18. Robustness Stress Testing in Medical Image Classification

    • Mobarakol Islam, Zeju Li, Ben Glocker
    Pages 167-176

  19. Confidence-Aware and Self-supervised Image Anomaly Localisation

    • Johanna P. Müller, Matthew Baugh, Jeremy Tan, Mischa Dombrowski, Bernhard Kainz
    Pages 177-187

  20. Uncertainty Estimation in Liver Tumor Segmentation Using the Posterior Bootstrap

    • Shishuai Wang, Johan Nuyts, Marina Filipovic
    Pages 188-197
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  1. Uncertainty for Safe Utilization of Machine Learning in Medical Imaging

Keywords

About this book

This book constitutes the refereed proceedings of the 5th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2023, held in conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. 

For this workshop, 21 papers from 32 submissions were accepted for publication. The accepted papers cover the fields of uncertainty estimation and modeling, as well as out of distribution management, domain shift robustness, Bayesian deep learning and uncertainty calibration.

Editors and Affiliations

  • University College London, London, UK

    Carole H. Sudre

  • University of Tübingen, Tübingen, Germany

    Christian F. Baumgartner

  • Harvard Medical School, Charlestown, USA

    Adrian Dalca

  • McGill University, Montreal, Canada

    Raghav Mehta

  • Imperial College London, London, UK

    Chen Qin

  • Department of Radiology, Brigham and Women’s Hospital, Boston, USA

    William M. Wells

Bibliographic Information

  • Book Title: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging

  • Book Subtitle: 5th International Workshop, UNSURE 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings

  • Editors: Carole H. Sudre, Christian F. Baumgartner, Adrian Dalca, Raghav Mehta, Chen Qin, William M. Wells

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-44336-7

  • 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 2023

  • Softcover ISBN: 978-3-031-44335-0Published: 07 October 2023

  • eBook ISBN: 978-3-031-44336-7Published: 06 October 2023

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XIII, 220

  • Number of Illustrations: 4 b/w illustrations, 54 illustrations in colour

  • Topics: Artificial Intelligence, Computer Imaging, Vision, Pattern Recognition and Graphics, Computing Milieux, Computer Applications

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