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Proceedings Paper

Vertebral degenerative disc disease severity evaluation using random forest classification
Author(s): Hector E. Munoz; Jianhua Yao; Joseph E. Burns; Yasuyuki Pham; James Stieger; Ronald M. Summers
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Paper Abstract

Degenerative disc disease (DDD) develops in the spine as vertebral discs degenerate and osseous excrescences or outgrowths naturally form to restabilize unstable segments of the spine. These osseous excrescences, or osteophytes, may progress or stabilize in size as the spine reaches a new equilibrium point. We have previously created a CAD system that detects DDD. This paper presents a new system to determine the severity of DDD of individual vertebral levels. This will be useful to monitor the progress of developing DDD, as rapid growth may indicate that there is a greater stabilization problem that should be addressed. The existing DDD CAD system extracts the spine from CT images and segments the cortical shell of individual levels with a dual-surface model. The cortical shell is unwrapped, and is analyzed to detect the hyperdense regions of DDD. Three radiologists scored the severity of DDD of each disc space of 46 CT scans. Radiologists’ scores and features generated from CAD detections were used to train a random forest classifier. The classifier then assessed the severity of DDD at each vertebral disc level. The agreement between the computer severity score and the average radiologist’s score had a quadratic weighted Cohen’s kappa of 0.64.

Paper Details

Date Published: 18 March 2014
PDF: 8 pages
Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90353A (18 March 2014); doi: 10.1117/12.2042793
Show Author Affiliations
Hector E. Munoz, National Institutes of Health (United States)
Jianhua Yao, National Institutes of Health (United States)
Joseph E. Burns, Univ. of California, Irvine (United States)
Yasuyuki Pham, Univ. of California, Irvine (United States)
James Stieger, National Institutes of Health (United States)
Ronald M. Summers, National Institutes of Health (United States)


Published in SPIE Proceedings Vol. 9035:
Medical Imaging 2014: Computer-Aided Diagnosis
Stephen Aylward; Lubomir M. Hadjiiski, Editor(s)

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