Measuring the Effect of Filters on Segmentation of Developmental Dysplasia of the Hip

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dc.contributor.authorKocer, Hasan Erdinc
dc.contributor.authorCevik, Kerim Kursat
dc.contributor.authorSivri, Mesut
dc.contributor.authorKoplay, Mustafa
dc.date.accessioned2020-03-26T19:25:03Z
dc.date.available2020-03-26T19:25:03Z
dc.date.issued2016
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractBackground: Developmental dysplasia of the hip(DDH) can be detected with ultrasonography (USG) images. However, the accuracy of this method is dependent on the skill of the radiologist. Radiologists measure the hip joint angles without computer-based diagnostic systems. This causes mistakes in the diagnosis of DDH. Objectives: In this study, we aimed to automate segmentation of DDH ultrasound images in order to make it convenient for radiologic diagnosis by this recommended system. Materials and Methods: This experiment consisted of several steps, in which pure DDH and various noise-added images were formed. Then, seven different filters (mean, median, Gaussian, Wiener, Perona and Malik, Lee, and Frost) were applied to the images, and the output images were evaluated. The study initially evaluated the filter implementations on the pure DDH images. Then, three different noise functions, speckle, salt and pepper, and Gaussian, were applied to the images and the noisy images were filtered. In the last part, the peak signal to noise ratio (PSNR) and mean square error (MSE) values of the filtered images were evaluated. PSNR and MSE distortion measurements were applied to determine the image qualities of the original image and the output image. As a result, the differences in the results of different noise removal filters were observed. Results: The best results of PSNR values obtained in filtering were: Wiener (43.49), Perona and Malik (27.68), median (40.60) and Lee (35.35) for the noise functions of raw images, Gaussian noise added, salt and pepper noise added and speckle noise added images, respectively. After the segmentation process, it was seen that applying filtering to DDH USG images had low influence. We correctly segmented the ilium zone with the active contour model. Conclusion: Various filters are needed to improve the image quality. In this study, seven different filters were implemented and investigated on both noisy and noise-free images.en_US
dc.identifier.doi10.5812/iranjradiol.25491en_US
dc.identifier.issn1735-1065en_US
dc.identifier.issn2008-2711en_US
dc.identifier.issue3en_US
dc.identifier.pmid27853489en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.urihttps://dx.doi.org/10.5812/iranjradiol.25491
dc.identifier.urihttps://hdl.handle.net/20.500.12395/33776
dc.identifier.volume13en_US
dc.identifier.wosWOS:000384820700004en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherKOWSAR PUBLen_US
dc.relation.ispartofIRANIAN JOURNAL OF RADIOLOGYen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectUltrasonographyen_US
dc.subjectImage Processingen_US
dc.subjectDevelopmental Dysplasia of the Hipen_US
dc.subjectFilteringen_US
dc.titleMeasuring the Effect of Filters on Segmentation of Developmental Dysplasia of the Hipen_US
dc.typeArticleen_US

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