The impact of CT-data segmentation variation on the morphology of osteological structure

Matthew Wysocki; Scott Doyle

doi:10.1117/12.2581122

15 February 2021 The impact of CT-data segmentation variation on the morphology of osteological structure

Matthew Wysocki, Scott Doyle

Proceedings Volume 11595, Medical Imaging 2021: Physics of Medical Imaging; 1159533 (2021) https://doi.org/10.1117/12.2581122
Event: SPIE Medical Imaging, 2021, Online Only

Conference Poster

Abstract

CT (computed tomography) scans have become indispensable tools for gross anatomy teaching and research [1-5]. Computational methods can create high-resolution 3D models of anatomical structures for education, research, and clinical applications [6-9]. However, data processing has a large influence on 3D model generation. Understanding how these differences in processing alter morphology, and whether such disparities impact the conclusions one may draw from the data, is imperative for interpreting radiology ground truth. Failure to account for these differences can lead to erroneous decisions regarding joint repair, joint replacement, and prosthetics design. In this work, we investigate how segmentation algorithms influence the morphology of 3D models of osteological structures (femurs) from human cadaveric CT scans. We measure dissimilarity in 3D model morphology resulting from multiple different segmentation protocols. As CT scanderived 3D models become more commonplace in gross anatomical research, it is critical to fully understand proper segmentation approaches and how much variation is acceptable for 3D anatomical models derived from radiological imaging.

Conference Presentation

Citation Download Citation

Matthew Wysocki and Scott Doyle "The impact of CT-data segmentation variation on the morphology of osteological structure", Proc. SPIE 11595, Medical Imaging 2021: Physics of Medical Imaging, 1159533 (15 February 2021); https://doi.org/10.1117/12.2581122

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available