Automatic segmentation of the optic nerves and chiasm in CT and MR using the atlas-navigated optimal medial axis and deformable-model algorithm

Jack H. Noble; Benoit M. Dawant

doi:10.1117/12.810941

27 March 2009 Automatic segmentation of the optic nerves and chiasm in CT and MR using the atlas-navigated optimal medial axis and deformable-model algorithm

Jack H. Noble, Benoit M. Dawant

Author Affiliations +

Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 725916 (2009) https://doi.org/10.1117/12.810941
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

In recent years, radiation therapy has become the preferred treatment for many types of head and neck tumors. To minimize side effects, radiation beams are planned pre-operatively to avoid over-radiation of vital structures, such as the optic nerves and chiasm, which are essential to the visual process. To plan the procedure, these structures must be identified using CT/MR imagery. Currently, a radiation oncologist must manually segment the structures, which is both inefficient and ineffective. Clearly an automated approach could be beneficial to the planning process. The problem is difficult due to the shape variability and low image contrast of the structures, and several attempts at automatic localization have been reported with marginal results. In this work we present a novel method for localizing the optic nerves and chiasm in CT/MR volumes using the atlas-navigated optimal medial axis and deformable-model algorithm (NOMAD). NOMAD uses a statistical model and image registration to provide a priori local intensity and shape information to both a medial axis extraction procedure and a deformable-model, which deforms the medial axis and completes the segmentation process. This approach achieves mean dice coefficients greater than 0.8 for both the optic nerves and the chiasm when compared to manual segmentations over ten test cases. By comparing quantitative results with existing techniques it can be seen that this method produces more accurate results.

Citation Download Citation

Jack H. Noble and Benoit M. Dawant "Automatic segmentation of the optic nerves and chiasm in CT and MR using the atlas-navigated optimal medial axis and deformable-model algorithm", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 725916 (27 March 2009); https://doi.org/10.1117/12.810941

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