A Novel Method for Lung Segmentation on Chest CT Images: Complex-Valued Artificial Neural Network with Complex Wavelet Transform

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dc.contributor.authorCeylan, Murat
dc.contributor.authorÖzbay, Yüksel
dc.contributor.authorUçan, O. Nuri
dc.contributor.authorYıldırım, Erkan
dc.date.accessioned2020-03-26T17:46:45Z
dc.date.available2020-03-26T17:46:45Z
dc.date.issued2010
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractImage segmentation is an important step in many computer vision algorithms. The objective of segmentation is to obtained an optimal region of convergences (ROC). Error in this stage will impact all higher level activities. This paper focuses on a new efficient method denoted as Complex-Valued Artificial Neural Network with Complex Wavelet Transform (CWT-CVANN) for the segmentation of lung region on chest CT images. In this combined architecture is composed of two cascade stages: feature extraction with various levels of complex wavelet transform, and segmentation with complex-valued artificial neural network. Hem, 32 CT images of 6 female and 26 male patients were recorded from, Baskent University Radiology Department. (This collection includes 10 images with benign nodules and 22 images with malign nodules. Averaged age of patients is 64. Each CT slice used in this study has dimensions of 752x 752 pixels with grey level) In only two seconds of processing time per each CT image, 99.79% averaged accuracy rate is obtained using 3(rd) level CWT-CVANN for segmentation of the lung region. Thus, it is concluded that CWT-CVANN is a comprising method in luny region segmentation problem.en_US
dc.identifier.citationCeylan, M., Özbay, Y., Uçan, O. N., Yıldırım, E., (2010). A Novel Method for Lung Segmentation on Chest CT Images: Complex-Valued Artificial Neural Network with Complex Wavelet Transform. Turkish Journal of Electrical Engineering and Computer Sciences, 18(4), 613-623. Doi: 10.3906/elk-0908-137
dc.identifier.doi10.3906/elk-0908-137en_US
dc.identifier.endpage623en_US
dc.identifier.issn1300-0632en_US
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage613en_US
dc.identifier.urihttps://dx.doi.org/10.3906/elk-0908-137
dc.identifier.urihttps://hdl.handle.net/20.500.12395/24536
dc.identifier.volume18en_US
dc.identifier.wosWOS:000281623300008en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.institutionauthorCeylan, Murat
dc.institutionauthorÖzbay, Yüksel
dc.language.isoenen_US
dc.publisherTubitak Scientific & Technical Research Council Turkeyen_US
dc.relation.ispartofTurkish Journal of Electrical Engineering and Computer Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectLung segmentationen_US
dc.subjectComplex wavelet transformen_US
dc.subjectComplex-valued artificial neural networken_US
dc.titleA Novel Method for Lung Segmentation on Chest CT Images: Complex-Valued Artificial Neural Network with Complex Wavelet Transformen_US
dc.typeArticleen_US

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