Paper
20 March 2015 Automatic sulcal curve extraction on the human cortical surface
Author Affiliations +
Abstract
The recognition of sulcal regions on the cortical surface is an important task to shape analysis and landmark detection. However, it is challenging especially in a complex, rough human cortex. In this paper, we focus on the extraction of sulcal curves from the human cortical surface. The previous sulcal extraction methods are time-consuming in practice and often have a difficulty to delineate curves correctly along the sulcal regions in the presence of significant noise. Our pipeline is summarized in two main steps: 1) We extract candidate sulcal points spread over the sulcal regions. We further reduce the size of the candidate points by applying a line simplification method. 2) Since the candidate points are potentially located away from the exact valley regions, we propose a novel approach to connect candidate sulcal points so as to obtain a set of complete curves (line segments). We have shown in experiment that our method achieves high computational efficiency, improved robustness to noise, and high reliability in a test-retest situation as compared to a well-known existing method.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ilwoo Lyu, Sun Hyung Kim, and Martin Styner "Automatic sulcal curve extraction on the human cortical surface", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94130P (20 March 2015); https://doi.org/10.1117/12.2078291
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Image segmentation

Distance measurement

Brain

Reliability

Medical imaging

Neuroimaging

Optical spheres

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