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Proceedings Paper

Improved automatic optic nerve radius estimation from high resolution MRI
Author(s): Robert L. Harrigan; Alex K. Smith; Louise A. Mawn; Seth A. Smith; Bennett A. Landman
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Paper Abstract

The optic nerve (ON) is a vital structure in the human visual system and transports all visual information from the retina to the cortex for higher order processing. Due to the lack of redundancy in the visual pathway, measures of ON damage have been shown to correlate well with visual deficits. These measures are typically taken at an arbitrary anatomically defined point along the nerve and do not characterize changes along the length of the ON. We propose a fully automated, three-dimensionally consistent technique building upon a previous independent slice-wise technique to estimate the radius of the ON and surrounding cerebrospinal fluid (CSF) on high-resolution heavily T2-weighted isotropic MRI. We show that by constraining results to be three-dimensionally consistent this technique produces more anatomically viable results. We compare this technique with the previously published slice-wise technique using a short-term reproducibility data set, 10 subjects, follow-up <1 month, and show that the new method is more reproducible in the center of the ON. The center of the ON contains the most accurate imaging because it lacks confounders such as motion and frontal lobe interference. Long-term reproducibility, 5 subjects, follow-up of approximately 11 months, is also investigated with this new technique and shown to be similar to short-term reproducibility, indicating that the ON does not change substantially within 11 months. The increased accuracy of this new technique provides increased power when searching for anatomical changes in ON size amongst patient populations.

Paper Details

Date Published: 24 February 2017
PDF: 7 pages
Proc. SPIE 10133, Medical Imaging 2017: Image Processing, 101331C (24 February 2017); doi: 10.1117/12.2254370
Show Author Affiliations
Robert L. Harrigan, Vanderbilt Univ. (United States)
Alex K. Smith, Vanderbilt Univ. (United States)
Louise A. Mawn, Vanderbilt Univ. (United States)
Seth A. Smith, Vanderbilt Univ. (United States)
Bennett A. Landman, Vanderbilt Univ. (United States)


Published in SPIE Proceedings Vol. 10133:
Medical Imaging 2017: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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