Intelligent Anatomic Models from CT Utilizing ML - Matt Shomper - Not a Robot

Organization:

Not a Robot

Presenter:

Matt Shomper

Recorded at CDFAM Computational Design Symposium, NYC, October 29-30, 2025https://cdfam.com/nyc-2025/

Intelligent Anatomic Models from CT Utilizing ML

Presentation Abstract

This presentation discusses an accessible system that takes CT scans and automatically turns them into detailed 3D models while intelligently tagging important anatomical features. Instead of engineers and researchers spending hours manually creating these models and identifying landmarks, our approach uses machine learning to do the heavy lifting.

The process works by feeding CT scan data through specialized algorithms that can recognize the structures and convert the flat scan slices into three-dimensional representations. At the same time, the system automatically identifies and labels key anatomical points like bone structures or tissue edges – creating a smart, annotated 3D map of what was scanned.

This has the ability to dramatically speed up workflows that previously required tedious manual work. The automated tagging means that medical professionals get consistent, standardized labels across different cases, which is especially valuable for surgical planning and patient-specific implants.

The presentation will cover some challenges of utilizing M/L, how manual inputs can train algorithms over time, and looking towards the future of validating such systems for true use in commercialized systems.

Speaker Bio

Matthew is a visionary leader in the computational design of advanced 3D-printed medical implants, with close to 15 years of experience in engineering, research, and innovation. As an inventor, creator, and passionate leader, he has been a part of founding businesses focused on additive manufacturing and is an internationally recognized speaker on biomimicry, computational modeling, and additive manufacturing – lecturing at conferences and prestigious universities including MIT and Harvard. Matthew’s work is driven by his passion for exploring the macro and micro of biological forms, turning algorithms into functional structures for physical devices. He has pioneered the idea of a “biologically advantageous implant,” and has also spearheaded multiple public initiatives to synthesize biological structures as computational models for use in engineered products. He currently is the founder and principal consultant of Not a Robot Engineering, a co-founder of LatticeRobot, and involved in several other stealth startups.

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