We gladly announce the workshop on Shape in Medical Imaging (ShapeMI), which is held in conjunction with the conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2023) in Vancouver, Canada. This workshop is the third instance of ShapeMI, after successful ShapeMI'18 and ShapeMI'20.

The goal of this workshop continues being a venue for the presentation of the leading methods and applications for advanced shape analysis and geometric learning in medical imaging. It will provide a venue for researchers working in shape/geometric modeling, learning, analysis, statistics, classification and applications to share novel ideas, to present recent research results and to interact with each other.

Today’s image data usually represents 3D geometric structures, often describing continuous and time-varying phenomena. Therefore, shape and geometry processing methods have been receiving increased attention, for example, due to their higher sensitivity to local variations relative to traditional markers, such as the volume of a structure. Shape and spectral analysis, learning and modeling algorithms, as well as application-driven research are at the focus of this workshop. In Medical Image Computing or Computer Aided Intervention, the understanding of shapes and their geometrical representations enables the modeling and analysis of organs, of anatomical or functional structures, as well as of high-dimensional structures in datasets representing population or disease data.

2023 Proceedings

https://link.springer.com/book/10.1007/978-3-031-46914-5

Topics

This workshop targets theoretical contributions as well as exciting applications in medical imaging, including (but not limited to):

• Shape Processing and Analysis
• Shape Learning and Classification
• Geometric Learning and Manifold-based Methods
• Statistics of Shapes and Deformations
• Geometry-constrained Deep Learning and Optimization
• Synthetic Anatomical Shape Generation
• Generative Shape Models
• Spectral Shape Analysis
• Spectral Clustering and Dimensionality Reduction
• Shape Modeling and Representation
• Shape Segmentation, Registration and Correspondence
• Longitudinal Shape Analysis and Processing
• Medical Applications Focused on Shape Analysis
• Evaluation / Quality Assessment of Shape Models
• Relevant Demos of Freely Available Shape Analysis Software

Academic objectives

This workshops aims at bringing together medical imaging scientists to discuss novel approaches and application in shape and geometry processing and their use in research and clinical studies and applications. Another aim is to explore novel, cutting-edge theoretical methods and their usefulness for medical applications, such as from the fields of geometric learning or spectral shape analysis. As a single-track workshop, ShapeMI will feature excellent keynote speakers, technical paper presentations and demonstrations of state-of-the-art software for shape processing in medical research.

Data (optional)

If you are looking for medical shapes for your work, take a look at MedShapeNet, which is a large-scale dataset of 3D medical shapes.

Organizers

• Christian Wachinger, Technical University of Munich, Munich, Germany
• Beatriz Paniagua, Kitware Inc. and University of North Carolina at Chapel Hill, USA
• Shireen Elhabian, School of Computing, Scientific Computing and Imaging Institute, University of Utah, USA
• Jianning Li, Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany
• Jan Egger, Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany

Advisory Board / Program Committee

• Ellen Gasparovic, Union College, New York, United States
• Guido Gerig, New York University, New York, United States
• James Fishbaugh, Kitware, New York, United States
• Jens Kleesiek, UK Essen, Essen, Germany
• Kathryn Leonard, Occidental College, Los Angeles, United States
• Miaomiao Zhang, University of Virginia, Virginia, United States
• Stefan Sommer, University of Copenhagen, Copenhagen, Denmark
• Steve Pizer, University of North Carolina at Chapel Hill, North Carolina, United States
• Tim Cootes, Manchester University, Manchester, England
• Umberto Castellani, University of Verona, Verona, Italy
• Yonggang Shi, University of Southern California, California, United States
• Veronika Zimmer, Technical University Munich, Munich, Germany
• Ilwoo Lyu, Ulsan National Institute of Science and Technology, Ulsan, South Korea
• Suyash Awate, Indian Institute of Technology, Bombay, India
• Sungmin Hong, AWS
• Ilkay Oksuz, Istanbul Technical University, Istanbul, Turkey

Best Paper Award

TBD