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  • Küçük Resim
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    Beyincik Sarkması Tip-I Hastalarında Beyincik Gri Maddesinin Fraktal Boyut Analizi
    (IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2015) Akar, Engin; Kara, Sadık; Akdemir, Hidayet; Kırış, Adem
    Chiari Malformation type I (CM-I), which is described as the elongation of cerebellar tonsils below the foramen magnum through the spinal canal, is a serious congenital or acquired neurological disorder. The purpose of the present study is to implement a fractal analysis using a single midline sagittal Magnetic Resonance Imaging (MRI) data to evaluate the morphological properties of cerebellar grey matter (GM) in CM-I patients. Therefore, MRI images of 17 patients and 16 healthy subjects were employed to determine the fractal dimension values of cerebellar GM. A custom built graphical user interface (GUI) program developed by MATLAB was used to manually extract the cerebellum to create binary masks. Methods of SPM software package were used to segment the GM from the whole image. With the help of binary cerebellar mask, cerebellar GM data were obtained. Finally, estimation of FD and area values for the segmented GM data were performed. The results indicated that FD values for cerebellar GM in patients with CM-I was significantly higher (p < 0.05) in comparison with those in control group. These findings suggest that FD values estimated for cerebellar GM tissue can serve as a useful marker, a discriminative and descriptive feature to investigate the abnormalities and irregularities in the cerebellum of patients with CM-I.
  • Küçük Resim
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    Fractal analysis of MR images in patients with chiari malformation: The importance of preprocessing
    (ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND, 2017) Akar, Engin; Kara, Sadık; Akdemir, Hidayet; Kırış, Adem
    As a popular method to meathe complexity of images and generally signals, FD analyses have been used in neuroimaging studies to evaluate the morphological complexity of brain structures. The aim of this study is to perform an FD-based complexity analyses of cerebellar tissues, such as cerebellar white matter (WM), cerebellar gray matter (GM) and cerebrospinal fluid (CSF) spaces around the cerebellum, on magnetic resonance (MR) images of Chiari Malformation type-I (CM-I) patients and healthy controls. Besides, to determine the noise effects on complexity of sub cerebellar structures, two common nonlinear noise filters, median filter and bilateral filter, were applied to MR images and their performances were compared. Data of fourteen CM-I patients and sixteen normal subjects were used in this study. First, noise variance was estimated using a method based on skewness of the magnitude data. Second, as a preprocessing step, median and bilateral filters were applied on MR data separately to create different series of images for each filter. After the preprocessing, filtered brain images were segmented into three different tissues including WM, GM and CSF. Last, a 3D box-counting method was applied on segmented images to estimate the corresponding FD values. Our results showed that, while GM FD values was not significantly different between patients and controls (p = 0.051) in median filtering case, GM FD values in patients were found to be significantly lower than those in controls (p = 0.007) in bilateral filtering case. Additionally, in both cases, WM FD values in patients were found to be significantly lower than those in controls; however, this difference was more evident in bilateral filtering case (p = 0.0003) than that in median filtering case (p = 0.013). These outcomes indicated that bilateral filter was found to be more successful in discriminating CM-I patients from controls in cerebellar complexity analyses. In conclusion, results of this study revealed that noise removal is an important preprocessing step for a more successful analysis of digital images and bilateral filter is an effective filtering method for segmentation accuracy and FD analysis performance.