An atlas-navigated optimal medial axis and deformable model algorithm (NOMAD) for the segmentation of the optic nerves and chiasm in MR and CT images.

Noble JH, Dawant BM
Med Image Anal. 2011 15 (6): 877-84

PMID: 21684796 · PMCID: PMC3191306 · DOI:10.1016/

In recent years, radiation therapy has become the preferred treatment for many types of head and neck tumors. To plan the procedure, vital structures, including the optic nerves and chiasm, must be identified using CT/MR imagery. In this work we present a novel method for automatically localizing the optic nerves and chiasm using a tubular structure localization algorithm in which a statistical model and image registration are used to incorporate a priori local intensity and shape information. The method results in mean Dice coefficients of 0.8 when compared to manual segmentations over ten test cases. This suggests that our method is more accurate than existing techniques developed for the segmentation of these structures.

Copyright © 2011 Elsevier B.V. All rights reserved.

MeSH Terms (9)

Algorithms Computer Simulation Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Optic Chiasm Optic Nerve Radiotherapy Planning, Computer-Assisted Tomography, X-Ray Computed

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