Purpose: The aim of this study was to analyze variations in the morphological features of the subparietal sulcus (SPS) and to investigate interhemispheric and gender differences in these variations using multiplanar reconstructed (MPR) magnetic resonance (MR) images.
Methods: Two hundred subjects with normal cranial MR imaging, including high-resolution T1-weighted volumetric data, were enrolled in the study. The sagittal or oblique sagittal MPR images created from high-resolution T1-weighted data were analyzed for the following morphological features: the SPS patterns, the continuity of the SPS with the cingulate sulcus and parieto-occipital sulcus (POS), and the presence of upwardly directed SPS branches reaching to the hemispheric surface.
This study aims classification of phosphorus magnetic resonance spectroscopic imaging ((31)P-MRSI) data of human brain tumors using machine-learning algorithms. The metabolite peak intensities and ratios were estimated for brain tumor and healthy (31)P MR spectra acquired at 3T. The spectra were classified based on metabolite characteristics using logistic regression and support vector machine.
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