Title

Additive Manufacturing for Medical Education

Author(s) Information

Michael Noon, California Polytechnic State University, San Luis ObispoFollow

College - Author 1

College of Engineering

Department - Author 1

Computer Engineering Department

Advisor

Xuan Wang, CENG, IME;Jenny Wang, CENG, CSE

Funding Source

Noyce School of Applied Computing

Acknowledgements

Open Source Developers (JSON for Modern C++, Lib3MF, OpenXLSX, Inipp, PrusaSlicer) and Jakob Wasserthal et al. (TotalSegmentator)

Date

10-2023

Abstract/Summary

A growing body of evidence is suggesting that anatomical knowledge, the keystone of many medical specialties, is suffering among new graduates. While a host of reasons are provided, one common thread that many point to is the decline of cadaver dissections in the classroom. Many virtual audio-visual tools are used to address this gap, yet evidence has shown their ineffectiveness. Given this gap, the high degree of flexibility found in additive manufacturing (AM), and the many uses AM has already found in the medical field, we propose its use to fill this gap, allowing for students to learn with touch in addition to sight and sound among a host of other benefits. Our proposed system is a modular workflow that covers the generation of highly detailed heterogenous digital model representations and manufacturing said digital representations. In service of this, a basic framework of this workflow was implemented on Windows operating systems to show the viability of used standards.

October 1, 2023.