Creating patient-specific anatomical models for 3D printing and AR/VR: a supplement for the 2018 Radiological Society of North America (RSNA) hands-on course

Nicole Wake,Amy E Alexander,Peter C Liacouras,Andy M Christensen,Jane Matsumoto,Maureen Schickel,Todd Pietila

doi:10.1186/s41205-019-0054-y

Abstract

Advanced visualization of medical image data in the form of three-dimensional (3D) printing continues to expand in clinical settings and many hospitals have started to adapt 3D technologies to aid in patient care. It is imperative that radiologists and other medical professionals understand the multi-step process of converting medical imaging data to digital files. To educate health care professionals about the steps required to prepare DICOM data for 3D printing anatomical models, hands-on courses have been delivered at the Radiological Society of North America (RSNA) annual meeting since 2014. In this paper, a supplement to the RSNA 2018 hands-on 3D printing course, we review methods to create cranio-maxillofacial (CMF), orthopedic, and renal cancer models which can be 3D printed or visualized in augmented reality (AR) or virtual reality (VR).

Highlights

Advanced medical image data visualization in the form of three-dimensional (3D) printing continues to expand in clinical settings
Many hospitals have started to adapt 3D technology to aid in patient care, for use in medical student education, and for research applications. 3D printing originated in the 1980s and encompasses various processes intended to generate a physical model from a digital file [1,2,3]
In order to generate patient-specific models for 3D printing and Augmented Reality (AR)/Virtual Reality (VR), anatomical structures are segmented from digital imaging and communications in medicine (DICOM) data and the generated structures are converted to virtual 3D models

Summary

Introduction

Advanced medical image data visualization in the form of three-dimensional (3D) printing continues to expand in clinical settings. Digital imaging and communications in medicine (DICOM) files cannot be used directly for 3D printing anatomical models. In order to generate patient-specific models for 3D printing and AR/VR, anatomical structures are segmented from DICOM data and the generated structures are converted to virtual 3D models.

Results

Conclusion