Pre-processing Effects of the Tuberculosis Chest X-Ray Images on Pre-trained CNNs: An Investigation

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dc.contributor.authorTasci, E.
dc.date.accessioned2020-12-01T11:52:51Z
dc.date.available2020-12-01T11:52:51Z
dc.date.issued2020
dc.departmentEge Üniversitesien_US
dc.description.abstractTuberculosis (TB) is a serious infectious disease which is one of the top causes of death worldwide. In 2017, 1.6 million people died from the disease according to the World Health Organization (WHO). The earlier identification and treatment of the TB is critical for preventing death and decreasing risk of transmitting the disease to others. Computer-aided diagnosis (CADx) systems are essential tools to speed up the decision-making process of experts and provide more efficient, accurate and systematic solutions. Chest radiography (CXR) is one of the most common and effective imaging technique for the detection of thoracic diseases such as TB and lung cancer. In this study, three different region of interests (ROIs) based pre-processing methods are applied to two CXR image datasets (namely, Montgomery and Shenzhen). We used three pre-trained convolutional neural networks (CNNs) (namely, AlexNet, VGG16, VGG19) as deep learning models and deep feature extractors for automatic classification of TB disease. We investigate the pre-processing effects of TB CXR images on the classifier whether ROI is selected and remaining regions of images are set pixel values to white, black and same pixel values in the original images. Experimental results indicate that proposed methods contribute to the classifier performance gain considerably in terms of accuracy rate. © 2020, Springer Nature Switzerland AG.en_US
dc.identifier.doi10.1007/978-3-030-36178-5_48
dc.identifier.endpage596en_US
dc.identifier.issn2367-4512
dc.identifier.issn2367-4512en_US
dc.identifier.scopus2-s2.0-85083444052en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage589en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-030-36178-5_48
dc.identifier.urihttps://hdl.handle.net/11454/61667
dc.identifier.volume43en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofLecture Notes on Data Engineering and Communications Technologiesen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClassificationen_US
dc.subjectConvolutional neural networksen_US
dc.subjectDeep learningen_US
dc.subjectDiagnosisen_US
dc.subjectMachine learningen_US
dc.subjectRegion of interesten_US
dc.subjectTuberculosisen_US
dc.titlePre-processing Effects of the Tuberculosis Chest X-Ray Images on Pre-trained CNNs: An Investigationen_US
dc.typeBook Chapteren_US

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