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Shape in Medical Imaging

International Workshop, ShapeMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Christian Wachinger

    1. Technical University of Munich, Munich, Germany

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  2. Beatriz Paniagua

    1. University of North Carolina at Chapel Hill, Carrboro, USA

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  3. Shireen Elhabian

    1. University of Utah, Salt Lake City, USA

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  4. Jianning Li

    1. Essen University Hospital, Essen, Germany

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  5. Jan Egger

    1. Essen University Hospital, Essen, Germany

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14350)

Included in the following conference series:

Conference proceedings info: ShapeMI 2023.

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Table of contents (23 papers)

  1. Front Matter

    Pages i-xi
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  2. Anatomy Completor: A Multi-class Completion Framework for 3D Anatomy Reconstruction

    • Jianning Li, Antonio Pepe, Gijs Luijten, Christina Schwarz-Gsaxner, Jens Kleesiek, Jan Egger
    Pages 1-14

  3. \(\hbox {C}^3\)Fusion: Consistent Contrastive Colon Fusion, Towards Deep SLAM in Colonoscopy

    • Erez Posner, Adi Zholkover, Netanel Frank, Moshe Bouhnik
    Pages 15-34

  4. Anatomy-Aware Masking for Inpainting in Medical Imaging

    • Yousef Yeganeh, Azade Farshad, Nassir Navab
    Pages 35-46

  5. Particle-Based Shape Modeling for Arbitrary Regions-of-Interest

    • Hong Xu, Alan Morris, Shireen Y. Elhabian
    Pages 47-54

  6. Optimal Coronary Artery Segmentation Based on Transfer Learning and UNet Architecture

    • Belén Serrano-Antón, Alberto Otero-Cacho, Diego López-Otero, Brais Díaz-Fernández, María Bastos-Fernández, Gemma Massonis et al.
    Pages 55-64

  7. Unsupervised Learning of Cortical Surface Registration Using Spherical Harmonics

    • Seungeun Lee, Sunghwa Ryu, Seunghwan Lee, Ilwoo Lyu
    Pages 65-74

  8. Unsupervised Correspondence with Combined Geometric Learning and Imaging for Radiotherapy Applications

    • Edward G. A. Henderson, Marcel van Herk, Andrew F. Green, Eliana M. Vasquez Osorio
    Pages 75-89

  9. ADASSM: Adversarial Data Augmentation in Statistical Shape Models from Images

    • Mokshagna Sai Teja Karanam, Tushar Kataria, Krithika Iyer, Shireen Y. Elhabian
    Pages 90-104

  10. Body Fat Estimation from Surface Meshes Using Graph Neural Networks

    • Tamara T. Mueller, Siyu Zhou, Sophie Starck, Friederike Jungmann, Alexander Ziller, Orhun Aksoy et al.
    Pages 105-117

  11. Geometric Learning-Based Transformer Network for Estimation of Segmentation Errors

    • Sneha Sree, Mohammad Al Fahim, Keerthi Ram, Mohanasankar Sivaprakasam
    Pages 118-132

  12. On the Localization of Ultrasound Image Slices Within Point Distribution Models

    • Lennart Bastian, Vincent Bürgin, Ha Young Kim, Alexander Baumann, Benjamin Busam, Mahdi Saleh et al.
    Pages 133-144

  13. FSJP-Net: Foreground and Shape Joint Perception Network for Glomerulus Detection

    • Qiuchi Han, Xiuxiu Hu, Pingsheng Chen, Siyu Xia
    Pages 145-156

  14. Progressive DeepSSM: Training Methodology for Image-To-Shape Deep Models

    • Abu Zahid Bin Aziz, Jadie Adams, Shireen Elhabian
    Pages 157-172

  15. Muscle Volume Quantification: Guiding Transformers with Anatomical Priors

    • Louise Piecuch, Vanessa Gonzales Duque, Aurélie Sarcher, Enzo Hollville, Antoine Nordez, Giuseppe Rabita et al.
    Pages 173-187

  16. Geodesic Logistic Analysis of Lumbar Spine Intervertebral Disc Shapes in Supine and Standing Positions

    • Ye Han, James Fishbaugh, Christian E. Gonzalez, Donald A. Aboyotes, Jared Vicory, Simon Y. Tang et al.
    Pages 188-200

  17. SlicerSALT: From Medical Images to Quantitative Insights of Anatomy

    • Jared Vicory, Ye Han, Juan Carlos Prieto, David Allemang, Mathieu Leclercq, Connor Bowley et al.
    Pages 201-210

  18. Predicting Shape Development: A Riemannian Method

    • DoÄŸa Türkseven, Islem Rekik, Christoph von Tycowicz, Martin Hanik
    Pages 211-222

  19. AReg IOS: Automatic Registration on IntraOralScans

    • Nathan Hutin, Luc Anchling, Lucia Cevidanes, Felicia Miranda, Denise Curado, Marcela Gurgel et al.
    Pages 223-235

  20. Modeling Longitudinal Optical Coherence Tomography Images for Monitoring and Analysis of Glaucoma Progression

    • James Fishbaugh, Ronald Zambrano, Joel S. Schuman, Gadi Wollstein, Jared Vicory, Beatriz Paniagua
    Pages 236-247
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  1. Shape in Medical Imaging

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About this book

This volume comprises the proceedings of the International Workshop, ShapeMI 2023, which took place alongside MICCAI 2023 on October 8, 2023, in Vancouver, British Columbia, Canada.

The 23 selected full papers deal with all aspects of leading methods and applications for advanced shape analysis and geometric learning in medical imaging.

Editors and Affiliations

  • Technical University of Munich, Munich, Germany

    Christian Wachinger

  • University of North Carolina at Chapel Hill, Carrboro, USA

    Beatriz Paniagua

  • University of Utah, Salt Lake City, USA

    Shireen Elhabian

  • Essen University Hospital, Essen, Germany

    Jianning Li, Jan Egger

Bibliographic Information

  • Book Title: Shape in Medical Imaging

  • Book Subtitle: International Workshop, ShapeMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

  • Editors: Christian Wachinger, Beatriz Paniagua, Shireen Elhabian, Jianning Li, Jan Egger

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-46914-5

  • 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 2023

  • Softcover ISBN: 978-3-031-46913-8Published: 31 October 2023

  • eBook ISBN: 978-3-031-46914-5Published: 30 October 2023

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XI, 302

  • Number of Illustrations: 4 b/w illustrations, 137 illustrations in colour

  • Topics: Image Processing and Computer Vision, Machine Learning, Special Purpose and Application-Based Systems

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