Sharif Digital Repository

Drug-resistant epilepsy is often associated with network disorders extending beyond a single focal area, and clinical decisions (including pre-surgical evaluation) depend on the accurate identification of the involved region٫network. This research presents a multimodal framework based on simultaneous EEG and resting-state fMRI data to distinguish "patient٫control" groups, aiming to analyze resting-state brain networks and extract potential biomarkers. The fMRI data was mapped to Regions of Interest (ROIs), and a sparse spatial graph was constructed based on k-nearest neighbors (kNN) adjacency between ROIs. The EEG data was segmented into short windows and aligned with the... 

Magnetic Resonance Imaging (MRI) is a non-invasive imaging modality which can represents the structure, metabolism and the function of inner tissues and organs. Unlike other imaging modalities MRI does not use ionizing radiation.Reducing the imaging time will result in cost reduction and patient comfort. Therefore since the invention of MRI, increasing the speed of imaging has drawn a lot of attention. This was mainly done by improving and upgrading the data collecting hardware of the imaging module.With the advances in technology, a point has been nearly reached, that due to the physical and physiological constraints, such as nerve stimulation, quickening the hardware is impractical.... 

Advancements in medical imaging, especially 3D imaging, leads to progressive growth of image processing for diagnosis, studying behavior of organs and development of disease. Therefore many researches have been done on segmentation, registration, modeling and 3D image refinement. In this thesis, we want to parameterize anatomic surfaces, using volume parameterization model.
Hippocampus is one of the most important components in brain that plays significant role in learning, memory, stress management and etc. There is been a theory that, shape and structure of hippocampus may change in diseases like Alzheimer, schizophrenia, chronic depression and epilepsy.
The aim of this research is... 

Exporting firms face a range of challenges when entering international markets, among which financial constraints are particularly significant. Financial constraints can impair a firm’s cash flow, making it difficult to finance the fixed costs associated with export market entry. This study constructs a firm-level index to measure the degree of financial constraint and examines its impact first on the probability of export participation, and then on the volume of exports. The analysis is based on data from Iran’s industrial firms between 2008 and 2019 (1387–1398 in the Iranian calendar). The effect of financial constraints on the probability of exporting is estimated using logit and linear... 

Diffusion Weighted Imaging (DWI) is a non-invasive method for investigating the brain white matter. Assuming the Gaussian model for diffusion process, diffusion tensor is constructed and Diffusion Tensor Images (DTI) are obtained. White matter is constructed from fiber bundles which have crossing in most of the regions. In the crossing regions, the Gaussian model cannot work. In this situation, DTI cannot reconstruct the fiber structures correctly. Therefore, High Angular Resolution Diffusion Imaging (HARDI) was proposed to solve this problem. Q-ball imaging is a new technique for HARDI reconstruction which is useful for estimating diffusion Orientation Distribution Function (ODF). ODF is a... 

Content Based Image Retrieval (CBIR) is in fact an image search engine which Operates on image Context . in this thesis (project) the aim was to use the Visual attention of humans in detecting the objects in image. in this ability first a salient image of the most important things in the image would be created And after an initial separation , for the final recognition the other features (details) in the image will be used It’s a while that the use of Visual attention models and saliency maps in designing the interfaces between humans and machines has been considered widely. This fact in the design of CBIR systems has not a good background (satisfying history). In this thesis I have... 

Based on Shannon theory, continuous-time band-limited signals are guaranteed to be recovered per-fectly subject to sampling with Nyquist rate. Due to inherently slow MRI sensors, sampling with Nyquist rate excruciatingly increases the scan time. This leads to patient inconvenience along with degradation in image quality caused by geometrical distortions.In recent years, Compressed Sensing (CS) has been introduced as an alternative to the Nyquist theory for the acquisition of sparse or compressible signals that can be well approximated by K ≪ N coeffi-cients from a N-dimensional basis. In CS theory, measurements are actually inner products of signal x with a base vector ϕi. In Fourier encoded... 

Image Registration is spatially alignment of two images in a wide range of applications such as remote sensing, computer assisted surgery, and medical image analysis and processing. In general, registration algorithms can be categorized as either intensity based or feature based. The feature based methods use the alignment between the extracted features in two images. The simplest feature is images intensity which is directly used in the intensity based method via similarity measure. This similarity measure quantifies the matching of two images.Similarity measure is main core of image registration algorithms. Spatially varying intensity dis-tortion is an important challenge in a wide range... 

Functional Magnetic Resonance Imaging (fMRI) is a recently developed neuroimaging technique with capacity to map neural activity with high spatial precision. To locate active brain areas, the method utilizes local blood oxygenation changes which are reflected as small intensity changes in a special type of MR images. The ability to non-invasively map brain functions provides new opportunities to unravel the mysteries and advance the understanding of the human brain, as well as to perform pre-surgical examinations in order to optimize surgical interventions. To obtain these goals the analysis of fMRI is the first condition which should be met. First methods were linear and assumed the... 

When medical imaging modalities are considered individually, they do not contain sufficient information of various aspects of a tissue. Medical image fusion methods have been proposed such that the information deficiency of each medical imaging modality, which is caused by inherent characteristics of imaging modalities, is eliminated and the resultant outputs contain more information than the individual modalities alone. This study proposes a novel method for medical image fusion of MRI and PET images based on progressive dual-discriminator GAN. The progressive part of the method, adds layers to the discriminators and generator in accordance with the resolution of down-scaled source images... 

Evidence shows that people with depressive disorder show altered functional connectivity in some of the parts of the brain. The functional characteristics of these brain areas in people with this disorder have not been completely determined. On the other hand, some researchers have rejected the static nature of functional connectivity and stated that functional connectivity changes over time. Measuring brain activity non-invasively with functional magnetic resonance imaging increases our understanding of brain organizations and functional mechanisms, so in this study, we used the functional magnetic resonance imaging data of 18 healthy subjects and 18 subjects with depression. Method: The... 

Image registration is the process of matching the coordinate systems of two or more images. Medical image registration has been used in a variety of applications such as segmentation, motion tracking and etc. Recently, the use of deep neural networks has been demonstrated as a useful approach to registration problems. In this work, we propose two separate novel Convolutional Neural Network (CNN) architectures for multi-modal rigid and affine registration of the CT-MRI images of the brain. A dataset consisting of CT-MRI images of 37 subjects was used for training and evaluation of the networks. For both networks, the proposed models achieved high mutual information value between predicted CT... 

Nowadays, image registration is considered as one of usual issues in medical researches whose new findings are expanding outstandingly and it has reached a high level of maturity. Generally speaking, image registration is a task to reliably estimate the geometric transformation such that two images can be precisely aligned. With respect to different uses of image registration in medical applications, it has attracted the attention of many scholars and there has been made significant improvement in this realm. Image registration is still one of the active branches in medical image processing due to its wide applications and problems. Graphs, thanks to their geometric structures and intuitive... 

Extracting the minutia of a fingerprint image and then hiding this information in the original image in order to increase the security has been explained and implemented in this thesis. One of the methods which can embed the predetermined digital data in the image is digital watermarking. In this thesis, the host image is a fingerprint image whose minutia has been embedded in that image. Embedding can be done in two spatial and frequency domains. In this thesis, embedding is implemented by combining two domains. Embedding in the frequency domain is applied to transforming coefficients directly from the image then by spatial method the information is embedded. Actually combining DWT and LSB... 

Content-based image retrieval (CBIR) is becoming an important field with the advance of multimedia and imaging technology everincreasingly. It makes use of image features, such as color, shape and texture, to index images with minimal human intervention. Among many retrieval features associated with CBIR, texture retrieval is one of the most powerful. Content-based image retrieval can also be utilized to locate medical images in large databases. In this research, we introduce a content-based approach to medical image retrieval. A case study, which describes the methodology of a CBIR system for retrieving digital human brain MRI database based on textural features retrieval, is then... 

Autism Spectrum Disorder (ASD) is a group of neurodevelopmental disorders that cause repetitive behaviors and social and communication skills abnormalities. Autistic Disorder(AD) is one of the disorders in ASD that is being investigated in this study. There has been an increase in research about AD in recent years due to the increasing AD prevalence and the high autistic living costs. The dynamic functional connectivity between healthy and autistic groups has been analyzed by using graph theory. The brain is modeled as a dynamic graph using resting-state fMRI. The graph theory metric is calculated in the dynamic graph of each subject, and the distinction of the two groups is checked using... 

Image registration is the process of estimating and applying a spatial transformation to a moving image with the aim of spatially aligning it with a fixed image. This allows for the combination of images with complementary information, such as images with different modalities, acquisition times, and even coming from separate individuals, with the purpose of producing more information-rich results. Image registration is a crucial step in many medical applications, such as analyzing the growth and changes of tissue and tumors, preoperative planning, image-guided surgery, radiation therapy planning and various segmentation tasks. Reinforcement learning is a science and mathematical paradigm for...