Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images

KOYUNCU, HASAN

Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images

Hasan KOYUNCU (Konya Technical University, Konya, Turkey)

International Journal of Intelligent Systems and Applications in Engineering

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Yıl: 2018 Cilt: 6 Sayı: 4 Sayfa Aralığı: 322 - 328 Metin Dili: İngilizce İndeks Tarihi: 24-09-2019

Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images

Öz:

Lung imaging and computer aided diagnosis (CAD) play a critical role in detection of lung diseases. The most significant partof a lung based CAD is to fulfil the parenchyma segmentation, since disease information is kept in the parenchyma texture. For this purpose,parenchyma segmentation should be accurately performed to find the necessary diagnosis to be used in the treatment. Besides, lungparenchyma segmentation remains as a challenging task in computed tomography (CT) owing to the handicaps oriented with the imagingand nature of parenchyma. In this paper, a cascade framework involving histogram analysis, morphological operations, mean shiftsegmentation (MSS) and region growing (RG) is proposed to perform an accurate segmentation in thorax CT images. In training data, 20axial CT images are utilized to define the optimum parameter values, and 150 images are considered as test data to objectively evaluatethe performance of system. Five statistical metrics are handled to carry out the performance assessment, and a literature comparison isrealized with the state-of-the-art techniques. As a result, parenchyma tissues are segmented with success rates as 98.07% (sensitivity),99.72% (specificity), 99.3% (accuracy), 98.59% (Dice similarity coefficient) and 97.23% (Jaccard) on test dataset.

Anahtar Kelime:

Konular: Bilgisayar Bilimleri, Yapay Zeka

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık

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APA	KOYUNCU H (2018). Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images. , 322 - 328.
Chicago	KOYUNCU HASAN Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images. (2018): 322 - 328.
MLA	KOYUNCU HASAN Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images. , 2018, ss.322 - 328.
AMA	KOYUNCU H Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images. . 2018; 322 - 328.
Vancouver	KOYUNCU H Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images. . 2018; 322 - 328.
IEEE	KOYUNCU H "Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images." , ss.322 - 328, 2018.
ISNAD	KOYUNCU, HASAN. "Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images". (2018), 322-328.

APA	KOYUNCU H (2018). Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images. International Journal of Intelligent Systems and Applications in Engineering, 6(4), 322 - 328.
Chicago	KOYUNCU HASAN Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images. International Journal of Intelligent Systems and Applications in Engineering 6, no.4 (2018): 322 - 328.
MLA	KOYUNCU HASAN Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images. International Journal of Intelligent Systems and Applications in Engineering, vol.6, no.4, 2018, ss.322 - 328.
AMA	KOYUNCU H Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images. International Journal of Intelligent Systems and Applications in Engineering. 2018; 6(4): 322 - 328.
Vancouver	KOYUNCU H Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images. International Journal of Intelligent Systems and Applications in Engineering. 2018; 6(4): 322 - 328.
IEEE	KOYUNCU H "Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images." International Journal of Intelligent Systems and Applications in Engineering, 6, ss.322 - 328, 2018.
ISNAD	KOYUNCU, HASAN. "Lupsix: A Cascade Framework for Lung Parenchyma Segmentation in Axial CT Images". International Journal of Intelligent Systems and Applications in Engineering 6/4 (2018), 322-328.