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Interpretability of Machine Intelligence in Medical Image Computing

5th International Workshop, iMIMIC 2022, Held in Conjunction with MICCAI 2022, Singapore, Singapore, September 22, 2022, Proceedings

  • Conference proceedings
  • © 2022

Overview

Editors:
  1. Mauricio Reyes

    1. University of Bern, Bern, Switzerland

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  2. Pedro Henriques Abreu

    1. University of Coimbra, Coimbra, Portugal

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    You can also search for this editor in PubMed   Google Scholar

  3. Jaime Cardoso

    1. University of Porto, Porto, Portugal

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13611)

Included in the following conference series:

Conference proceedings info: iMIMIC 2022.

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Table of contents (10 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Interpretable Lung Cancer Diagnosis with Nodule Attribute Guidance and Online Model Debugging

    • Hanxiao Zhang, Liang Chen, Minghui Zhang, Xiao Gu, Yulei Qin, Weihao Yu et al.
    Pages 1-11

  3. Do Pre-processing and Augmentation Help Explainability? A Multi-seed Analysis for Brain Age Estimation

    • Daehyun Cho, Christian Wallraven
    Pages 12-21

  4. Towards Self-explainable Transformers for Cell Classification in Flow Cytometry Data

    • Florian Kowarsch, Lisa Weijler, Matthias Wödlinger, Michael Reiter, Margarita Maurer-Granofszky, Angela Schumich et al.
    Pages 22-32

  5. Reducing Annotation Need in Self-explanatory Models for Lung Nodule Diagnosis

    • Jiahao Lu, Chong Yin, Oswin Krause, Kenny Erleben, Michael Bachmann Nielsen, Sune Darkner
    Pages 33-43

  6. Attention-Based Interpretable Regression of Gene Expression in Histology

    • Mara Graziani, Niccolò Marini, Nicolas Deutschmann, Nikita Janakarajan, Henning Müller, María Rodríguez Martínez
    Pages 44-60

  7. Beyond Voxel Prediction Uncertainty: Identifying Brain Lesions You Can Trust

    • Benjamin Lambert, Florence Forbes, Senan Doyle, Alan Tucholka, Michel Dojat
    Pages 61-70

  8. Interpretable Vertebral Fracture Diagnosis

    • Paul Engstler, Matthias Keicher, David Schinz, Kristina Mach, Alexandra S. Gersing, Sarah C. Foreman et al.
    Pages 71-81

  9. Multi-modal Volumetric Concept Activation to Explain Detection and Classification of Metastatic Prostate Cancer on PSMA-PET/CT

    • R. C. J. Kraaijveld, M. E. P. Philippens, W. S. C. Eppinga, I. M. Jürgenliemk-Schulz, K. G. A. Gilhuijs, P. S. Kroon et al.
    Pages 82-92

  10. KAM - A Kernel Attention Module for Emotion Classification with EEG Data

    • Dongyang Kuang, Craig Michoski
    Pages 93-103

  11. Explainable Artificial Intelligence for Breast Tumour Classification: Helpful or Harmful

    • Amy Rafferty, Rudolf Nenutil, Ajitha Rajan
    Pages 104-123

  12. Back Matter

    Pages 125-125
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  1. Interpretability of Machine Intelligence in Medical Image Computing

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About this book

This book constitutes the refereed joint proceedings of the 5th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2022,  held in September 2022, in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022.

The 10 full papers presented at iMIMIC 2022 were carefully reviewed and selected from 24 submissions each. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. 


Editors and Affiliations

  • University of Bern, Bern, Switzerland

    Mauricio Reyes

  • University of Coimbra, Coimbra, Portugal

    Pedro Henriques Abreu

  • University of Porto, Porto, Portugal

    Jaime Cardoso

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