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An identification methods of under-segmented regions in segmented lung mask
Author(s): Haiyan Wei; Changli Feng; Xin Li; Zhaogui Ma; Deyun Yang
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Paper Abstract

The Juxtapleural nodule regions are often missed in the result of lung segmentation algorithms. To tackle this problem, an identification method basing on the SIFT information and elliptic Fourier descriptor is proposed. Firstly, the SIFT information is used to locate the position of key points in the lung mask. Then with the help of distance relationship, the support borderlines of key points are calculated. Thirdly, the elliptic Fourier descriptor is introduced to describe a support line. Finally, an adaptive threshold is designed to decide whether the current support line is corresponding to an under-segmented region. Experiments on real CT images demonstrate that the proposed model provides an efficient way to perform under-segmented region identification task.

Paper Details

Date Published: 3 January 2020
PDF: 8 pages
Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 1137309 (3 January 2020); doi: 10.1117/12.2557234
Show Author Affiliations
Haiyan Wei, Taishan Univ. (China)
Changli Feng, Taishan Univ. (China)
Xin Li, Taishan Univ. (China)
Zhaogui Ma, Taishan Univ. (China)
Deyun Yang, Taishan Univ. (China)


Published in SPIE Proceedings Vol. 11373:
Eleventh International Conference on Graphics and Image Processing (ICGIP 2019)
Zhigeng Pan; Xun Wang, Editor(s)

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