Hossam Hassan

Reduced Gyral Window and Corpus Callosum Size in Autism: Possible Macroscopic Correlates of a Minicolumnopathy

Minicolumnar changes that generalize throughout a significant portion of the cortex have macroscopic structural correlates that may be visualized with modern structural neuroimaging techniques. In magnetic resonance images (MRIs) of fourteen autistic patients and 28 controls, the present study found macroscopic morphological correlates to recent neuropathological findings suggesting a minicolumnopathy in autism. Autistic patients manifested a significant reduction in the aperture for afferent/efferent cortical connections, i.e., gyral window. Furthermore, the size of the gyral window directly correlated to the size of the corpus callosum. A reduced gyral window constrains the possible size of projection fibers and biases connectivity towards shorter corticocortical fibers at the expense of longer association/commisural fibers. The findings may help explain abnormalities in motor skill development, differences in postnatal brain growth, and the regression of acquired functions observed in some autistic patients.

Adaptive Segmentation of Multi-modal 3D Data Using Robust Level Set Techniques

A new 3D segmentation method based on the level set technique is proposed. The main contribution is a robust evolutionary model which requires no fine tuning of parameters. A closed 3D surface propagates from an initial position towards the desired region boundaries through an iterative evolution of a specific 4D implicit function. Information about the regions is involved by estimating, at each iteration, parameters of probability density functions. The method can be applied to different kinds of data, e.g for segmenting anatomical structures in 3D magnetic resonance images and angiography. Experimental results of these two types of data are discussed.

Cerebrovascular segmentation for MRA data using level sets

Abstract In this paper, we use a level set based segmentation algorithm to extract the vascular tree from Phase Contrast Magnetic Resonance Angiography, “PCMRA”. Classification model finds an optimal partition of homogeneous classes with regular interfaces. Regions and their interfaces are represented by level set functions. The algorithm initializes level sets in each image slice using automatic seed initialization and then iteratively, each level set approaches the steady state and contains the vessel or non-vessel area. The results are validated using a phantom that simulates the “PCMRA”. The approach is fast and accurate. Results on various cases demonstrate the accuracy of the approach.

Effect of minicolumnar disturbance on dyslexic brains: an MRI study

The minicolumn is generally considered the basic unit of the neocortex in all the mammalian brains. Enlargement of the cortical surface is believed to occur through the addition of minicolumns rather than a single neuron. This study aims at testing the hypothesis that brain developmental disorders can be diagnosed and analyzed in terms of the minicolumnar disturbance. To do this, we propose to correlate the pathological findings in terms of the minicolumnar structure to the MRI findings in terms of volumetric analysis