Saadallah Ramadan

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Magnetic resonance (MR) imaging is a widely available and well accepted non invasive imaging technique. Development of automatic and semi-automatic techniques to analyse MR images has been the focus of much research and numerous publications. However, most of this research only uses the magnitude of the acquired complex MR signal, discarding the phase(More)
Exploiting the speed benefits of echo-planar imaging (EPI), the echo-planar spectroscopic imaging (EPSI) sequence facilitates recording of one spectral and two to three spatial dimensions faster than the conventional magnetic resonance spectroscopic imaging (MRSI). A novel four dimensional (4D) echo-planar correlated spectroscopic imaging (EP-COSI) was(More)
The goal was to identify which neurochemicals differ in professional athletes with repetitive brain trauma (RBT) when compared to healthy controls using a relatively new technology, in vivo Localized COrrelated SpectroscopY (L-COSY). To achieve this, L-COSY was used to examine five former professional male athletes with 11 to 28 years of exposure to contact(More)
Partial volume effects have the potential to cause inaccuracies when quantifying metabolites using proton magnetic resonance spectroscopy (MRS). In order to correct for cerebrospinal fluid content, a spectroscopic voxel needs to be segmented according to different tissue contents. This article aims to detail how automated partial volume segmentation can be(More)
Spinal cord injury (SCI) can be accompanied by chronic pain, the mechanisms for which are poorly understood. Here we report that magnetic resonance spectroscopy measurements from the brain, collected at 3T, and processed using wavelet-based feature extraction and classification algorithms, can identify biochemical changes that distinguish control subjects(More)
This paper considers the problem of automatic classification of textured tissues in 3D MRI. More specifically, it aims at validating the use of features extracted from the phase of the MR signal to improve texture discrimination in bone segmentation. This extra information provides better segmentation, compared to using magnitude only features. We also(More)
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