TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14365/4

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Publication Index: search.filters.publicationIndex.ScopusSubject: search.filters.subject.Radyoloji, Nükleer Tıp, Tıbbi Görüntüleme

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  • Article
    Can Volumetric Magnetic Resonance Imaging Evaluations Be Helpful in the Follow-Up of Cognitive Functions in Cognitively Normal Parkinson's Disease Patients?
    (Tubitak Scientific & Technological Research Council Turkey, 2024-08-23) Uysal, Hasan Armağan; Hunerli, Duygu; Çakmur, Raif; Dönmez Çolakoğlu, Beril; Ada, Emel; Yener, Görsev; Çolakoğlu, Beril Dönmez
    Background/aim: In this study, besides the evaluation of gray and white matter changes in cognitively normal Parkinson's disease (PDCN) patients with volumetric magnetic resonance imaging (MRI) parameters, it was tried to show that some neuropsychological tests may be impaired in PD-CN patients. Materials and methods: Twenty-six PD-CN patients and 26 healthy elderly (HC) participants were included in the current study. Global cognitive status was assessed using the mini-mental state examination (MMSE), and the Montreal cognitive assessment scale (MoCA). Attention and executive functions were evaluated using the Wechsler memory scale-revised (WMS-R) digit span test and trail making test (TMT) part A and part B, the Stroop test, semantic and phonemic fluency tests, and clock drawing test. Magnetic resonance imaging (MRI) was acquired according to the Alzheimer's disease neuroimaging initiative (ADNI) protocol. Results: There were no significant differences among groups regarding age, sex, handedness, and years of education. In the comparison of the PD-CN group and the HC group, there was a statistical decrease in the total animal scores, lexical fluency, TMT part A and TMT part B scores in the PD-CN group. Subcortical gray matter volumes (GMV) were significantly lower in PD-CN patients. The PD-CN group had a significantly reduced total volume of right putamen and left angular gyrus compared to that in the HC group. We observed that putamen and angular gyrus volumes were lower in PD-CN patients. On the other hand, TMT part B may be a useful pretest in detecting the conversion of mild cognitive impairment in PD. Conclusion: Significant MRI volumetric measurements and neuropsychological test batteries can be helpful in the clinical follow-up in PD-CN patients.
  • Article
    Citation - WoS: 7
    Citation - Scopus: 10
    Investigation of the Role of Convolutional Neural Network Architectures in the Diagnosis of Glaucoma Using Color Fundus Photography
    (Turkish Ophthalmological Soc, 2022-06-29) Atalay, Eray; Ozalp, Onur; Devecioglu, Ozer Can; Erdogan, Hakika; İnce, Türker; Yildirim, Nilgun
    Objectives: To evaluate the performance of convolutional neural network (CNN) architectures to distinguish eyes with glaucoma from normal eyes. Materials and Methods: A total of 9,950 fundus photographs of 5,388 patients from the database of Eskisehir Osmangazi University Faculty of Medicine Ophthalmology Clinic were labelled as glaucoma, glaucoma suspect, or normal by three different experienced ophthalmologists. The categorized fundus photographs were evaluated using a state-of-the-art two-dimensional CNN and compared with deep residual networks (ResNet) and very deep neural networks (VGG). The accuracy, sensitivity, and specificity of glaucoma detection with the different algorithms were evaluated using a dataset of 238 normal and 320 glaucomatous fundus photographs. For the detection of suspected glaucoma, ResNet-101 architectures were tested with a data set of 170 normal, 170 glaucoma, and 167 glaucoma-suspect fundus photographs. Results: Accuracy, sensitivity, and specificity in detecting glaucoma were 96.2%, 99.5%, and 93.7% with ResNet-50; 97.4 degrees A, 97.8%, and 97.1% with ResNet-101; 98.9%, 100%, and 98.1% with VGG-19, and 99.4%, 100%, and 99% with the 2D CNN, respectively. Accuracy, sensitivity, and specificity values in distinguishing glaucoma suspects from normal eyes were 62%, 68%, and 56% and those for differentiating glaucoma from suspected glaucoma were 92%, 81%, and 97%, respectively. While 55 photographs could be evaluated in 2 seconds with CNN, a clinician spent an average of 24.2 seconds to evaluate a single photograph. Conclusion: An appropriately designed and trained CNN was able to distinguish glaucoma with high accuracy even with a small number of fundus photographs. Conclusion: An appropriately designed and trained CNN was able to distinguish glaucoma with high accuracy even with a small number of fundus photographs.