@inproceedings{2d103fb783ea477083fd005da1f4db92,
title = "Pulmonary parenchyma segmentation in thin CT image sequences with spectral clustering and geodesic active contour model based on similarity",
abstract = "While the popular thin layer scanning technology of spiral CT has helped to improve diagnoses of lung diseases, the large volumes of scanning images produced by the technology also dramatically increase the load of physicians in lesion detection. Computer-aided diagnosis techniques like lesions segmentation in thin CT sequences have been developed to address this issue, but it remains a challenge to achieve high segmentation efficiency and accuracy without much involvement of human manual intervention. In this paper, we present our research on automated segmentation of lung parenchyma with an improved geodesic active contour model that is geodesic active contour model based on similarity (GACBS). Combining spectral clustering algorithm based on Nystrom (SCN) with GACBS, this algorithm first extracts key image slices, then uses these slices to generate an initial contour of pulmonary parenchyma of un-segmented slices with an interpolation algorithm, and finally segments lung parenchyma of un-segmented slices. Experimental results show that the segmentation results generated by our method are close to what manual segmentation can produce, with an average volume overlap ratio of 91.48%.",
author = "Nana He and Xiaolong Zhang and Juanjuan Zhao and Huilan Zhao and Yan Qiang",
note = "Funding Information: This work was supported by the National Nature Science Foundation of China (Grant Nos. 61373100 and 61540007) and National Key Laboratory of Open Foundation (Grant Nos. BUAA-VR-15KF02 and BUAA-VR-16KF-13). Publisher Copyright: {\textcopyright} 2017 SPIE.; 9th International Conference on Digital Image Processing, ICDIP 2017 ; Conference date: 19-05-2017 Through 22-05-2017",
year = "2017",
doi = "10.1117/12.2281942",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Xudong Jiang and Falco, {Charles M.}",
booktitle = "Ninth International Conference on Digital Image Processing, ICDIP 2017",
address = "United States",
}