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Computer Optics, 2017, Volume 41, Issue 5, Pages 726–731 (Mi co443)  

IMAGE PROCESSING, PATTERN RECOGNITION

Pulmonary emphysema recognition by CT scan

N. A. Smelkinaa, A. V. Kolsanovb, S. S. Chaplyginb, P. M. Zelterb, A. G. Khramova

a Samara National Research University, Samara, Russia
b Samara State Medical University, Samara, Russia

Abstract: We discuss a simple method for automatic recognition of pulmonary emphysema in three-dimensional computer tomography (CT) images. This technique allows one to quantify the disease progress, calculating some numerical characteristics, such as the percentage of the lung tissue affected, as well as visualizing its location and intensity histogram in the region of interest. An experiment on the test data shows that the recognition error is not higher than 7.5%.

Keywords: CT scan, pulmonary emphysema, diagnostic images, pathology segmentation, data mining.

Funding Agency Grant Number
Министерство промышленности и торговли Российской Федерации 4.3-Автоплан-2014
The work was performed as part of the Autoplan project (automatic system of planning and monitoring of the operation) under the state R & D contract Development of technology and organization of production of automated systems for planning, management and monitoring of surgical treatment outcome ("4.3-Autoplan-2014").


DOI: https://doi.org/10.18287/2412-6179-2017-41-5-726-731

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Full text: http://www.computeroptics.smr.ru/.../410516.html
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Received: 28.01.2017
Accepted:25.08.2017

Citation: N. A. Smelkina, A. V. Kolsanov, S. S. Chaplygin, P. M. Zelter, A. G. Khramov, “Pulmonary emphysema recognition by CT scan”, Computer Optics, 41:5 (2017), 726–731

Citation in format AMSBIB
\Bibitem{SmeKolCha17}
\by N.~A.~Smelkina, A.~V.~Kolsanov, S.~S.~Chaplygin, P.~M.~Zelter, A.~G.~Khramov
\paper Pulmonary emphysema recognition by CT scan
\jour Computer Optics
\yr 2017
\vol 41
\issue 5
\pages 726--731
\mathnet{http://mi.mathnet.ru/co443}
\crossref{https://doi.org/10.18287/2412-6179-2017-41-5-726-731}


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