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    Deep learning model for automated kidney stone detection using coronal CT images
    (Pergamon-Elsevier Science Ltd, 2021) Yildirim, Kadir; Bozdag, Pinar Gundogan; Talo, Muhammed; Yildirim, Ozal; Karabatak, Murat; Acharya, U. Rajendra
    Kidney stones are a common complaint worldwide, causing many people to admit to emergency rooms with severe pain. Various imaging techniques are used for the diagnosis of kidney stone disease. Specialists are needed for the interpretation and full diagnosis of these images. Computer-aided diagnosis systems are the practical approaches that can be used as auxiliary tools to assist the clinicians in their diagnosis. In this study, an automated detection of kidney stone (having stone/not) using coronal computed tomography (CT) images is proposed with deep learning (DL) technique which has recently made significant progress in the field of artificial intelligence. A total of 1799 images were used by taking different cross-sectional CT images for each person. Our developed automated model showed an accuracy of 96.82% using CT images in detecting the kidney stones. We have observed that our model is able to detect accurately the kidney stones of even small size. Our developed DL model yielded superior results with a larger dataset of 433 subjects and is ready for clinical application. This study shows that recently popular DL methods can be employed to address other challenging problems in urology.
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    Handedness related differences in bone mineral density in patients with osteoporosis
    (2013) Malkoc, Ismail; Dane, Şenol; Karatay, Saliha; Uzkeser, Hülya; Saruhan, Zeynep; Yildirim, Kadir
    Objective Left-handedness was reported to be associated with lower bone mineral density in a recent study and also to be a risk factor for accident-related injuries, head injuries, traumatic brain injuries, sport-related injuries and bone breaks and fractures. Therefore, the bone mineral densities of 17 left-handed patients with osteoporosis were compared to those of 141 right-handed ones in 14 males and 144 females. Methods Hand preference was assessed using the Edinburgh Handedness Inventory. To measure the bone mineral density, a Hologic QDR-4500W (S/N 48403) densitometer was used. Multivariate analysis of variance was used for the statistical evaluation. Results The bone mineral densities were higher in the right-handed patients with osteoporosis than in the left-handed ones. Conclusions These results support the claim that the left-handed patients with osteoporosis had higher bone damage risk in traumas and accidents. © 2013 Elsevier GmbH. © 2014 Elsevier B.V., All rights reserved.