Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Ma, Junchaoa | Yu, Nana; * | Shen, Congb | Wang, Zhiminc | He, Taipinga | Guo, You-minb
Affiliations: [a] Department of Radiology, The Affiliated Hospital of Shaanxi University of traditional Chinese Medicine, Xian yang, China | [b] Department of Radiology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China | [c] Department of Radiology, Tumor Hospital of Gansu Province, Lanzhou, China
Correspondence: [*] Corresponding author: Nan Yu, Department of Radiology, The Affiliated Hospital of Shaanxi University of traditional Chinese Medicine, 2# Wei Yang western Road, Xian Yang 712000, China. Tel.: +86 029 33320881; Fax: +86 029 33320881; E-mail: [email protected].
Abstract: BACKGROUND: This study aims to develop a computerized scheme that utilizes a differential geometric approach to identify pulmonary vessels and then evaluate the performance of the scheme on the CT images of heavy smokers. METHODS: The scheme consists of two primary steps to segment entire lung vascular tree and identify the number of pulmonary vessels in a cross section. The scheme performance including accuracy, consistency, and efficiency was assessed using 102 chest CT scans. Further assessment was performed on the relationship between pulmonary vessels and the extent of emphysema as well as pulmonary artery alteration. RESULTS: The mean number of vessels in the cross section at the 5th generation was 17.84±4.74 and 17.23±4.85 assessed by computerized scheme and radiologists, respectively, which are significantly different (t = 2.12, p = 0.055). The results were consistent with those obtained by using a semi-automatic tool (r = 0.75, p = 0.01). In addition, in the 5th generation, the mean number of vessels was inversely related to the percentage of the low attenuation area (r = –0.704, p = 0.000), the mean lumen area of pulmonary vessel was inversely related to the mean value of main pulmonary artery diameter (r = –0.617, p = 0.000). The computational time of segmenting vessels was 6.50±0.02 seconds, which is much less than the average 8 minutes of the time spent by radiologists using the semi-automatic tool. CONCLUSION: Applying the computerized scheme yields reasonable performance on the segmentation of pulmonary vessels. The alteration of pulmonary vessels may reflect the presence of pulmonary hypertension, as well as the extent of emphysema.
Keywords: Emphysema, computed tomography, pulmonary vessel, smoke, chronic obstructive pulmonary disease
DOI: 10.3233/XST-16216
Journal: Journal of X-Ray Science and Technology, vol. 25, no. 3, pp. 391-402, 2017
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]