Dr. Anthony Gatti (Stanford University Radiology): “Neural Implicit Representations For Understanding Musculoskeletal Health & Disease “

Speaker: Dr. Anthony Gatti (Stanford University Radiology)

Title: Neural Implicit Representations For Understanding Musculoskeletal Health & Disease 

Video:

Abstract:  Quantifying musculoskeletal geometry from medical imaging is a critical bottleneck in both clinical assessment and biomechanical modeling. This talk presents generative neural implicit representations (“Neural Shape Models”) as a scalable solution for encoding anatomic shape variability across populations. We show how the learned latent space of these models can predict disease onset and progression, and how they enable automated construction of patient-specific 3D models for physics-based simulation of tissue mechanics. Together, these tools offer a new paradigm for understanding musculoskeletal health and disease at scale.

Bio:  Anthony is an Instructor in the Department of Radiology, Stanford Univerity, and a member of the Wu Tsai Human Performance Alliance Digital Athlete team. His research develops AI-based approaches to quantifying musculoskeletal geometry extracted from medical imaging and integrates it into physics-based simulations to better understand musculoskeletal health and disease. Anthony is a Junior Fellow of the International Society of Magnetic Resonance in Medicine, and won the 2025 Promising Scientist Award from the International Society for Biomechanics. ​