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dc.contributor.authorMemis, Abbas
dc.contributor.authorBilgili, Fuat
dc.contributor.authorVARLI, Songül
dc.date.accessioned2021-12-10T10:33:23Z
dc.date.available2021-12-10T10:33:23Z
dc.identifier.citationMemis A., VARLI S., Bilgili F., "A novel approach for computerized quantitative image analysis of proximal femur bone shape deformities based on the hip joint symmetry", ARTIFICIAL INTELLIGENCE IN MEDICINE, cilt.115, 2021
dc.identifier.issn0933-3657
dc.identifier.othervv_1032021
dc.identifier.otherav_46a6d3ac-cf84-458a-8954-1803eff442bb
dc.identifier.urihttp://hdl.handle.net/20.500.12627/170117
dc.identifier.urihttps://doi.org/10.1016/j.artmed.2021.102057
dc.description.abstractAs a result of most of the bone disorders seen in hip joints, shape deformities occur in the structural form of the hip joint components. Image-based quantitative analysis and assessment of these deformities in bone shapes are very important for the evaluation, treatment, and prognosis of the various hip joint bone disorders. In this article, a novel approach for the image-based computerized quantitative analysis of proximal femur shape deformities is presented. In the proposed approach, shape deformities of the pathological proximal femurs were quantified over the contralateral healthy proximal femur shape structure of the same patient in 2D by taking the hip joint symmetry property of human anatomy into consideration. It is based on the idea that if the right and left proximal femurs in bilateral hip joints are highly symmetrical and also if one of the proximal femurs is healthy and the contralateral one is pathological, the non-overlapping bone shape regions can represent the deformities in pathological proximal femurs when both proximal femurs are registered to overlap each other. In the methodological process of the proposed study, a set of image preprocessing operations was primarily performed on the raw magnetic resonance imaging (MRI) data. Then, the segmented proximal femurs in bilateral hip joint images were automatically aligned with the Iterative Closest Point (ICP) rigid registration method. Following the registration, a set of image postprocessing operations was performed on the images of proximal femurs aligned. In the quantification phase, the bone shape deformities in pathological proximal femurs were quantified simply in terms of the mismatching area in 2D by measuring a shape variation index representing the total bone shape deformity ratio. To evaluate the proposed quantitative shape analysis approach, bilateral hip joints in a total of 13 coronal MRI sections of 13 patients with Legg-Calve-Perthes disease (LCPD) were used. Experimental studies have shown that the proposed approach has quite promising results in the quantitative representation of the pathological proximal femur shape deformities. Furthermore, consistent results have been observed for the Waldenstro center dot m classification stages of the disease. The shape deformity ratios in pathological proximal femurs were quantified as 9.44% (+/- 1.40), 18.38% (+/- 6.30), 24.73% (+/- 12.42), and 27.66% (+/- 10.41), respectively for the Initial, Fragmentation, Reossification, and Remodelling stages of LCPD with the quantification error rates of 0.29% (+/- 0.16), 0.58% (+/- 0.71), 1.12% (+/- 0.82), and 0.80% (+/- 0.98). Additionally, a mean error rate of 0.65% (+/- 0.68) was observed for the quantified shape deformity ratios of all samples.
dc.language.isoeng
dc.subjectAlgoritmalar
dc.subjectBiyomedikal Mühendisliği
dc.subjectMühendislik ve Teknoloji
dc.subjectGeneral Engineering
dc.subjectArtificial Intelligence
dc.subjectGeneral Computer Science
dc.subjectEngineering (miscellaneous)
dc.subjectBiomedical Engineering
dc.subjectComputer Science (miscellaneous)
dc.subjectBioengineering
dc.subjectComputer Vision and Pattern Recognition
dc.subjectComputer Science Applications
dc.subjectHealth Informatics
dc.subjectPhysical Sciences
dc.subjectHealth Sciences
dc.subjectBiyoistatistik ve Tıp Bilişimi
dc.subjectBilgisayar Bilimleri
dc.subjectMÜHENDİSLİK, BİYOMEDİKSEL
dc.subjectMühendislik
dc.subjectTIBBİ BİLİŞİM
dc.subjectKlinik Tıp
dc.subjectKlinik Tıp (MED)
dc.subjectTıp
dc.subjectTemel Tıp Bilimleri
dc.subjectSağlık Bilimleri
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectBilgisayar Bilimi
dc.subjectBİLGİSAYAR BİLİMİ, YAPAY ZEKA
dc.titleA novel approach for computerized quantitative image analysis of proximal femur bone shape deformities based on the hip joint symmetry
dc.typeMakale
dc.relation.journalARTIFICIAL INTELLIGENCE IN MEDICINE
dc.contributor.departmentYıldız Teknik Üniversitesi , ,
dc.identifier.volume115
dc.contributor.firstauthorID2686248


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