Anatomy Completor: A Multi-class Completion Framework for 3D Anatomy Reconstruction -- C3Fusion: Consistent Contrastive Colon Fusion, Towards Deep SLAM in Colonoscopy -- Anatomy-Aware Masking for Inpainting in Medical Imaging -- Particle-Based Shape Modeling for Arbitrary Regions-of-Interest -- Optimal coronary artery segmentation based on transfer learning and UNet architecture -- Unsupervised Learning of Cortical Surface Registration using Spherical Harmonics -- Unsupervised correspondence with combined geometric learning and imaging for radiotherapy applications -- ADASSM: Adversarial Data Augmentation in Statistical Shape Models From Images -- Body Fat Estimation from Surface Meshes using Graph Neural Networks -- Geometric Learning-Based Transformer Network for Estimation of Segmentation Errors -- On the Localization of Ultrasound Image Slices within Point Distribution Models -- FSJP-Net: Foreground and Shape Joint Perception Network for Glomerulus Detection -- Progressive DeepSSM: Training Methodology for Image-To-Shape Deep Models -- Muscle volume quantification: guiding transformers with anatomical priors -- Geodesic Logistic Analysis of Lumbar Spine Intervertebral Disc Shapes in Supine and Standing Positions -- SlicerSALT: From medical images to quantitative insights of anatomy -- Predicting Shape Development: A Riemannian Method -- AReg IOS: Automatic Registration on IntraOralScans -- Modeling Longitudinal Optical Coherence Tomography Images for Monitoring and Analysis of Glaucoma Progression -- IcoConv : Explainable brain cortical surface analysis for ASD classification -- DeCA: A Dense Correspondence Analysis Toolkit for Shape Analysis -- 3D Shape Analysis of Scoliosis -- SADIR: Shape-Aware Diffusion Models for 3D Image Reconstruction. .

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.