Document Type

Article

Publication Date

2020

DOI

10.1117/1.Jmi.7.1.015002

Publication Title

Journal of Medical Imaging

Volume

7

Issue

1

Pages

015002 (37 pp.)

Abstract

Purpose: We describe a shape-aware multisurface simplex deformable model for the segmentation of healthy as well as pathological lumbar spine in medical image data.

Approach: This model provides an accurate and robust segmentation scheme for the identification of intervertebral disc pathologies to enable the minimally supervised planning and patient-specific simulation of spine surgery, in a manner that combines multisurface and shape statistics-based variants of the deformable simplex model. Statistical shape variation within the dataset has been captured by application of principal component analysis and incorporated during the segmentation process to refine results. In the case where shape statistics hinder detection of the pathological region, user assistance is allowed to disable the prior shape influence during deformation.

Results: Results demonstrate validation against user-assisted expert segmentation, showing excellent boundary agreement and prevention of spatial overlap between neighboring surfaces. This section also plots the characteristics of the statistical shape model, such as compactness, generalizability and specificity, as a function of the number of modes used to represent the family of shapes. Final results demonstrate a proof-of-concept deformation application based on the open-source surgery simulation Simulation Open Framework Architecture toolkit.

Conclusions: To summarize, we present a deformable multisurface model that embeds a shape statistics force, with applications to surgery planning and simulation.

Comments

"SPIE grants to authors (and their employers) of papers, posters, and presentation recordings published in SPIE Proceedings or SPIE Journals on the SPIE Digital Library (hereinafter "publications") the right to post an author-prepared version or an official version (preferred version) of the publication on an internal or external server controlled exclusively by the author/employer or the entity funding the research, provided that (a) such posting is noncommercial in nature and the publication is made available to users without charge; (b) an appropriate copyright notice and citation appear with the publication; and (c) a link to SPIE's official online version of the publication is provided using the item's DOI."

© 2020 SPIE

Publisher's version available at: https://doi.org/10.1117/1.JMI.7.1.015002

Original Publication Citation

Haq, R., Schmid, J., Borgie, R., Cates, J., & Audette, M. A. (2020). Deformable multisurface segmentation of the spine for orthopedic surgery planning and simulation. Journal of Medical Imaging, 7(1), 015002. doi:10.1117/1.Jmi.7.1.015002

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