Sulci segmentation using geometric active contours

Mahsa Torkaman; Liangjia Zhu; Peter Karasev; Allen Tannenbaum

doi:10.1117/12.2249716

24 February 2017 Sulci segmentation using geometric active contours

Mahsa Torkaman, Liangjia Zhu, Peter Karasev, Allen Tannenbaum

Proceedings Volume 10133, Medical Imaging 2017: Image Processing; 101330I (2017) https://doi.org/10.1117/12.2249716
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

Sulci are groove-like regions lying in the depth of the cerebral cortex between gyri, which together, form a folded appearance in human and mammalian brains. Sulci play an important role in the structural analysis of the brain, morphometry (i.e., the measurement of brain structures), anatomical labeling and landmark-based registration.1 Moreover, sulcal morphological changes are related to cortical thickness, whose measurement may provide useful information for studying variety of psychiatric disorders. Manually extracting sulci requires complying with complex protocols, which make the procedure both tedious and error prone.2 In this paper, we describe an automatic procedure, employing geometric active contours, which extract the sulci. Sulcal boundaries are obtained by minimizing a certain energy functional whose minimum is attained at the boundary of the given sulci.

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Mahsa Torkaman, Liangjia Zhu, Peter Karasev, and Allen Tannenbaum "Sulci segmentation using geometric active contours", Proc. SPIE 10133, Medical Imaging 2017: Image Processing, 101330I (24 February 2017); https://doi.org/10.1117/12.2249716

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