Imaging the human body

Understanding the arrangement of bone, muscle, and fat tissue in the human body has been essential for diagnosing disease and developing personalised digital twins. While imaging modalities such as CT and MRI provided accurate internal measurements, they required bulky, expensive equipment, expert operators, and time-consuming procedures.

Optical body scanning emerged as a faster and more affordable modality with improving spatial resolution, though it remained limited to capturing only the skin surface. By combining optical scanning with statistical models of human anatomy—derived from large datasets of internal body scans—the project aimed to enable rapid, low-cost scanning of individuals to estimate their internal anatomy.

A custom high-resolution 3D body scanner was developed and used to begin imaging participants of varying body shapes. The project then worked toward creating personalised whole-body anatomical scaffolds from these scans.

The approach included:

• Fitting statistical shape models of the body surface (using the STAR model) to participant scans.
• Estimating bone anatomy through a coupled body-surface and bone statistical model (using the OSSO model).
• Using these estimated internal landmarks to guide scaffold fitting and construction.