Yazar "Sahin, Bunyamin" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim Yok
    Öğe
    Investigation of total cerebellar and flocculonodular lobe volume in Parkinson's disease and healthy individuals: a brain segmentation study
    (Springer-Verlag Italia Srl, 2024) Ozgen, Merve Nur; Sahin, Necati Emre; Ertan, Nurcan; Sahin, Bunyamin
    Background Parkinson's disease (PD) is a neurodegenerative disorder with an unexplored link to the cerebellum. In the pathophysiology of balance disorders in PD, the role of the flocculonodular lobe (FL) is linked to the impairment of the dopaminergic system. Dopamine deficiency can also lead to changes in cerebellum functions, disrupting balance control. This study compares cerebellar and FL volumes between healthy controls (HC) and PD patients, analyzing their correlation with clinical outcomes. Methods We used magnetic resonance images of 23 PD patients (14 male, 9 female) and 24 HC (9 male, 15 female). Intracranial (ICV), total cerebellar, FL, and cerebellar gray matter volumes were measured using VolBrain. Clinical outcomes in PD patients were assessed using the Unified Parkinson's Disease Rating Scale (UPDRS-III) to evaluate motor function, with scores correlated to volumetric data. Results The cerebellar and gray matter volumes in HC were 115.53 +/- 10.44 cm(3) and 84.83 +/- 7.76 cm(3), respectively, compared to 126.83 +/- 13.47 cm(3) and 92.37 +/- 9.45 cm(3) in PD patients, indicating significantly larger volumes in PD patients (p < 0.05). The flocculonodular lobe gray matter volume was 1.14 +/- 0.19 cm(3) in PD patients and 1.02 +/- 0.13 cm(3) in HC, but there was a significant increase in gray matter volume in PD patients between the groups (p < 0.05). In PD patients, significant negative correlations were observed between FL volume and the UPDRS-III scores (r = - 0.467, p = 0.033) and between UPDRS-III scores and both total (r = - 0.453, p = 0.039) and normalized (r = - 0.468, p = 0.032) gray matter volumes of the FL. Conclusion Although total gray matter volumes were larger in PD patients, the volumes of FL did not differ between groups. In Parkinson's disease, increased cerebellar volume may regulate fine motor movements rather than balance.
  • Küçük Resim Yok
    Öğe
    Sex estimation using sternum part lenghts by means of artificial neural networks
    (Elsevier Ireland Ltd, 2019) Oner, Zulal; Turan, Muhammed Kamil; Oner, Serkan; Secgin, Yusuf; Sahin, Bunyamin
    In addition to the pelvis, cranium and phalanges, the sternum is also used for postmortem sex identification. Bone measurements may be obtained on cadaveric bones. Alternatively, computerized tomography may be used to obtain measurements close to the original ones. Moreover, usage of artificial neural networks (ANNs) in the field of medicine has started to provide new horizons. In this study, we aimed to identify sex by an ANN using lengths of manubrium sterni (MSL), corpus sterni (CSL) and processus xiphoideus (XPL) and sternal angle (SA) from computerized tomography (CT) images brought to an orthogonal plane. This study used the thin-slice thoracic CT images of 422 cases (213 female, 209 male) with an age range of 27-60 years brought to the orthogonal plane. Measurements of MSL, CSL, XPL and SA were analyzed with a multilayer artificial neural network that used stochastic gradient descent (SGD) for optimization and two hidden layers. MSL, CSL and XPL were longer, and SA was wider in men (MSL p = 0.000, CSL p = 0.000, XPL p = 0.000, SA p = 0.02). In the case of the two hidden layers of the network with 20 and 14 neurons in the hidden layers, respectively, learning rate of 0.1 and momentum coefficient of 0.9, the accuracy (Acc) of sex prediction was 0.906. In order to define a more realistic performance of the network, bootstrap was run with the confidence interval of 94%. A sensitivity (Sen) value of 0.91 and a specificity (Spe) value of 0.90 were calculated. The success rates that were achieved in sex identification with measurements on the skeleton using ANN were observed to be higher than those achieved by linear models. Also, sometimes all parts of the bones may not be found or might be deformed. In this case, the number of parameters used for the estimation will be incomplete. The ANN has the strong advantage to be able to estimate despite the missing parameter. (C) 2019 Elsevier B.V. All rights reserved.