Sharif Digital Repository

The functional network of the human brain is altered in many neurological and psychiatric disorders. Characterizing brain activity in terms of functionally segregated regions does not reveal anything about the communication among different brain regions and how such inter-communication could influence neural activity in each local region. The aim of this project is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the simulated, realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral... 

This thesis proposes a novel method for enhancing the image signal based on compressed sensing. Compressed sensing, as a new rapidly growing research field, promises to effectively recover a sparse signal at the rate of below Nyquist rate. This revolutionary technology strongly relies on the sparsity of the signal and incoherency between sensing basis and representation basis. Exact recovery of a sparse signal will be occurred in a situation that the signal of interest sensed randomly and the measurements are also taken based on sparsity level and log factor of the signal dimension. In this research, compressed sensing method is proposed to reduce the noise and reconstruct the image signal....