Fatemeh Ahmadi

Fatemeh Ahmadi, Mohamad Ebrahim Shiri, Behroz Bidabad et al.

Automated feature extraction from MRI brain scans and diagnosis of Alzheimer's disease are ongoing challenges. With advances in 3D imaging technology, 3D data acquisition is becoming more viable and efficient than its 2D counterpart. Rather than using feature-based vectors, in this paper, for the first time, we suggest a pipeline to extract novel covariance-based descriptors from the cortical surface using the Ricci energy optimization. The covariance descriptors are components of the nonlinear manifold of symmetric positive-definite matrices, thus we focus on using the Gaussian radial basis function to apply manifold-based classification to the 3D shape problem. Applying this novel signature to the analysis of abnormal cortical brain morphometry allows for diagnosing Alzheimer's disease. Experimental studies performed on about two hundred 3D MRI brain models, gathered from Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset demonstrate the effectiveness of our descriptors in achieving remarkable classification accuracy.

Fatemeh Jamal, Fatemeh Ahmadi, Mohammad Khanzadeh et al.

Nowadays for measurement of refractive index of nanomaterials usually spectro-photometric and mechanical methods are used which are expensive and indirect. In this paper for measuring these parameters of zinc oxide nanomaterial with two different stabilizers, a simple optical method, Moire deflectometry, which is based on wave front analysis and geometric optics is used. In the Moire deflectometry method, the beam of light from the laser diode passes through the sample. As a result of that, a change in the sample environment is observed as deflections of the fringes. By recording of these deflections using CCD and image processing with MATLAB, the nanomaterials refractive indices can be calculated. Due to the high accuracy of this method and improved the image processing code in Matlab, the smallest changes of the refractive index in the sample can be measured. Digital Image processing is used for processing images in a way that features can be selected and being shown. The results obtained in this method show a good improvement over the other used methods.