Sharif Digital Repository

One of the most important issues in medical image processing is the registration of images with various imaging modalities, because in this case, one can take advantage of these imaging modalities and sometimes fuse and use the useful information of each one in the form of a single image.As it was said, MRI and ultrasound images each have their own disadvantages and advantages, and by considering these two modalities, they have tried to integrate the good features of these two. As we know, one of the destructive cases in the MRI image is the inhomogeneity of the image, a inhomogeneity due to the fact that the main magnetic field is not constant and makes the parts of the image brighter or... 

Despite intensive scientific investigations, drug addiction treatment outcomes have not significantly improved in more than 30 years. The addicted human brain can be conceptualized as a set of networks that spatially and temporally interact with each other in an abnormal way. Over the past several decades, neuroimaging techniques have contributed important novel insights into the neuroplastic alterations that result from drug dependence. Also functional connectivity magnetic resonance imaging (fcMRI) has emerged as a powerful tool for mapping large-scale networks in the human brain. On the other hand, transcranial direct current stimulation (tDCS) has been reintroduced as a noninvasive brain... 

The registration of images is a fundamental task in numerous applications in medical image processing. The importance of medical image registraiton due to the imaging systems development in last decades is obvious to every one. Especially the wide employment and different capabilities of these systems has caused more attention to this field of image processing. Th e application of medical image registraiton is extended from clinical diagnosis and treatment evaluation, to image guided surgery. The dimension of images as well as modalities of imaging and imaging subjectshas made a wide variety of problems in this branch of image processing. Registration, briefly speaking, is a geometrical... 

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... 

Memory and recalling process has always been a basic question. Decoding the Long-Term_Memory is one of the first steps in answering this question. Since various experiments in the field of human long-term memory, was conducted. This research is motivated by a trial that in which, the Mgntvansfalvgram (MEG) has been recorded while recalling the color and orientation of a grading which is associated with an object, after the object has been shown. High accuracy in Decoding the mentioned color and direction, will be decoding the long-term memory. In order to enhance memory decoding, the research studies different classifiers such as sparse based classifiers and other popular one. It has also... 

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... 

Image registration is fundamental in medical imaging, enabling the accurate alignment and analysis of images from different modalities. This process is essential for various applications, including the assessment of tissue growth and tumor evolution, preoperative and intraoperative planning, and segmentation. While recent advances in deep learning have improved unsupervised monomodal medical image registration, these methods typically rely on transforming images and computing a similarity loss function between the transformed and target images. However, for multimodal image registration, traditional similarity functions often lack expressiveness and are prone to numerous local optima. To... 

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...