dc.citation.conferencePlace |
US |
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dc.citation.title |
Medical Imaging 2015: Image Processing |
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dc.contributor.author |
Lyu, Ilwoo |
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dc.contributor.author |
Kim, S.H. |
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dc.contributor.author |
Styner, M. |
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dc.date.accessioned |
2023-12-19T22:41:23Z |
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dc.date.available |
2023-12-19T22:41:23Z |
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dc.date.created |
2021-03-09 |
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dc.date.issued |
2015-02-24 |
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dc.description.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 SPIE. |
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dc.identifier.bibliographicCitation |
Medical Imaging 2015: Image Processing |
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dc.identifier.doi |
10.1117/12.2078291 |
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dc.identifier.issn |
1605-7422 |
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dc.identifier.scopusid |
2-s2.0-84943390973 |
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dc.identifier.uri |
https://scholarworks.unist.ac.kr/handle/201301/50152 |
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dc.language |
영어 |
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dc.publisher |
SPIE |
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dc.title |
Automatic sulcal curve extraction on the human cortical surface |
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dc.type |
Conference Paper |
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dc.date.conferenceDate |
2015-02-24 |
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