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Medical Optical Imaging and Virtual Microscopy Image Analysis

First International Workshop, MOVI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings

  • Conference proceedings
  • © 2022

Overview

Editors:
  1. Yuankai Huo

    1. Vanderbilt University, Nashville, USA

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  2. Bryan A. Millis

    1. Vanderbilt Biophotonics Center, Nashville, USA

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  3. Yuyin Zhou

    1. University of California, Santa Cruz, Santa Cruz, USA

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  4. Xiangxue Wang

    1. Nanjing University of Information Science and Technology, Nanjing, China

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  5. Adam P. Harrison

    1. Q Bio, San Carlos, USA

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  6. Ziyue Xu

    1. Nvidia Corporation, Santa Clara, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13578)

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Conference proceedings info: MOVI 2022.

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About this book

This book constitutes the refereed proceedings of the 1st International Workshop on Medical Optical Imaging and Virtual Microscopy Image Analysis, MOVI 2022, held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022, in Singapore, Singapore, in September 2022.


The 18 papers presented at MOVI 2022 were carefully reviewed and selected from 25 submissions. The objective of the MOVI workshop is to promote novel scalable and resource-efficient medical image analysis algorithms for high-dimensional image data analy-sis, from optical imaging to virtual microscopy.

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Table of contents (18 papers)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Cell Counting with Inverse Distance Kernel and Self-supervised Learning

    • Yue Guo, David Borland, Carolyn McCormick, Jason Stein, Guorong Wu, Ashok Krishnamurthy
    Pages 1-10

  3. Predicting the Visual Attention of Pathologists Evaluating Whole Slide Images of Cancer

    • Souradeep Chakraborty, Rajarsi Gupta, Ke Ma, Darshana Govind, Pinaki Sarder, Won-Tak Choi et al.
    Pages 11-21

  4. Edge-Based Self-supervision for Semi-supervised Few-Shot Microscopy Image Cell Segmentation

    • Youssef Dawoud, Katharina Ernst, Gustavo Carneiro, Vasileios Belagiannis
    Pages 22-31

  5. Joint Denoising and Super-Resolution for Fluorescence Microscopy Using Weakly-Supervised Deep Learning

    • Colin S. C. Tsang, Tony C. W. Mok, Albert C. S. Chung
    Pages 32-41

  6. MxIF Q-score: Biology-Informed Quality Assurance for Multiplexed Immunofluorescence Imaging

    • Shunxing Bao, Jia Li, Can Cui, Yucheng Tang, Ruining Deng, Lucas W. Remedios et al.
    Pages 42-52

  7. A Pathologist-Informed Workflow for Classification of Prostate Glands in Histopathology

    • Alessandro Ferrero, Beatrice Knudsen, Deepika Sirohi, Ross Whitaker
    Pages 53-62

  8. Leukocyte Classification Using Multimodal Architecture Enhanced by Knowledge Distillation

    • Litao Yang, Deval Mehta, Dwarikanath Mahapatra, Zongyuan Ge
    Pages 63-72

  9. Deep Learning on Lossily Compressed Pathology Images: Adverse Effects for ImageNet Pre-trained Models

    • Maximilian Fischer, Peter Neher, Michael Götz, Shuhan Xiao, Silvia Dias Almeida, Peter Schüffler et al.
    Pages 73-83

  10. Profiling DNA Damage in 3D Histology Samples

    • Kristofer E. delas Peñas, Ralf Haeusler, Sally Feng, Valentin Magidson, Mariia Dmitrieva, David Wink et al.
    Pages 84-93

  11. Few-Shot Segmentation of Microscopy Images Using Gaussian Process

    • Surojit Saha, Ouk Choi, Ross Whitaker
    Pages 94-104

  12. Adversarial Stain Transfer to Study the Effect of Color Variation on Cell Instance Segmentation

    • Huaqian Wu, Nicolas Souedet, Camille Mabillon, Caroline Jan, Cédric Clouchoux, Thierry Delzescaux
    Pages 105-114

  13. Constrained Self-supervised Method with Temporal Ensembling for Fiber Bundle Detection on Anatomic Tracing Data

    • Vaanathi Sundaresan, Julia F. Lehman, Sean Fitzgibbon, Saad Jbabdi, Suzanne N. Haber, Anastasia Yendiki
    Pages 115-125

  14. Sequential Multi-task Learning for Histopathology-Based Prediction of Genetic Mutations with Extremely Imbalanced Labels

    • Haleh Akrami, Tosha Shah, Amir Vajdi, Andrew Brown, Radha Krishnan, Razvan Cristescu et al.
    Pages 126-135

  15. Morph-Net: End-to-End Prediction of Nuclear Morphological Features from Histology Images

    • Gozde N. Gunesli, Robert Jewsbury, Shan E Ahmed Raza, Nasir M. Rajpoot
    Pages 136-144

  16. A Light-Weight Interpretable Model for Nuclei Detection and Weakly-Supervised Segmentation

    • Yixiao Zhang, Adam Kortylewski, Qing Liu, Seyoun Park, Benjamin Green, Elizabeth Engle et al.
    Pages 145-155

  17. A Coarse-to-Fine Segmentation Methodology Based on Deep Networks for Automated Analysis of Cryptosporidium Parasite from Fluorescence Microscopic Images

    • Ziheng Yang, Halim Benhabiles, Feryal Windal, Jérôme Follet, Anne-Charlotte Leniere, Dominique Collard
    Pages 156-166

  18. Swin Faster R-CNN for Senescence Detection of Mesenchymal Stem Cells in Bright-Field Images

    • Chunlun Xiao, Mingzhu Li, Liangge He, Xuegang Song, Tianfu Wang, Baiying Lei
    Pages 167-176

  19. Characterizing Continual Learning Scenarios for Tumor Classification in Histopathology Images

    • Veena Kaustaban, Qinle Ba, Ipshita Bhattacharya, Nahil Sobh, Satarupa Mukherjee, Jim Martin et al.
    Pages 177-187

  20. Back Matter

    Pages 189-190
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Other volumes

  1. Medical Optical Imaging and Virtual Microscopy Image Analysis

Editors and Affiliations

  • Vanderbilt University, Nashville, USA

    Yuankai Huo

  • Vanderbilt Biophotonics Center, Nashville, USA

    Bryan A. Millis

  • University of California, Santa Cruz, Santa Cruz, USA

    Yuyin Zhou

  • Nanjing University of Information Science and Technology, Nanjing, China

    Xiangxue Wang

  • Q Bio, San Carlos, USA

    Adam P. Harrison

  • Nvidia Corporation, Santa Clara, USA

    Ziyue Xu

Bibliographic Information

  • Book Title: Medical Optical Imaging and Virtual Microscopy Image Analysis

  • Book Subtitle: First International Workshop, MOVI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings

  • Editors: Yuankai Huo, Bryan A. Millis, Yuyin Zhou, Xiangxue Wang, Adam P. Harrison, Ziyue Xu

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-16961-8

  • 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 2022

  • Softcover ISBN: 978-3-031-16960-1Published: 17 September 2022

  • eBook ISBN: 978-3-031-16961-8Published: 16 September 2022

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XI, 190

  • Number of Illustrations: 3 b/w illustrations, 60 illustrations in colour

  • Topics: Computer Imaging, Vision, Pattern Recognition and Graphics, Artificial Intelligence, Computers and Education, Computer Applications

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