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An adaptive morphology template methods for correcting lung juxtapleural nodules regions in CT images
Author(s): Changli Feng; Haiyan Wei; Xin Li; Zhaogui Ma; Sai Qiao; Deyun Yang
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Paper Abstract

Lung juxtapleural nodule regions are often excluded from the extracted lung region by the intensity information-based methods. In order to solve this problem, an adaptive morphology template method is proposed. First of all, the SIFT information is used to extract some feature points in the borderline. Then, the Fourier descriptor is introduced to identify those juxtapleural nodule regions from all borderline sections. Finally, adaptive morphology templates are used to correct the recognized region. Through the experiments on real CT slices, perfect correction effect proves that the proposed model has a good power of re-correction for CT images.

Paper Details

Date Published: 3 January 2020
PDF: 10 pages
Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 113731X (3 January 2020); doi: 10.1117/12.2557222
Show Author Affiliations
Changli Feng, Taishan Univ. (China)
Haiyan Wei, Taishan Univ. (China)
Xin Li, Taishan Univ. (China)
Zhaogui Ma, Taishan Univ. (China)
Sai Qiao, 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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