Sharif Digital Repository

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... 

In this research a novel method is proposed which uses the concept of image registration to forecast frames as a new frame up conversion method. This frame rate up conversion method is specially designed for medical videos because of the medical structure of the none rigid image registration used as a field to forecast new frames which causes better results for these kinds of videos. In this method we interpolate new frames in the field of none rigid transformation grid in order to improve video parameters such as blocking, blurriness, etc. which can help doctors to detect abnormalities in such videos much preciously. By analyzing existing methods, we can find that this field is bereft of a... 

Predicting protein function accurately is an important issue in the post genomic era. To achieve this goal, several approaches have been proposed deduce the function of unclassified proteins through sequence similarity, co expression profiles, and other information. Among these methods, the Global Optimization Method is an interesting and powerful tool that assigns functions to unclassified proteins based on their positions in a physical interaction network. To boost both the accuracy and speed of global optimization method, a new prediction method, Accurate Global Optimization Method (AGOM), is presented in this thesis, which employs optimal repetition method enhanced with frequency of... 

Efficient feature selection from images would lead to a lower operational cost in image processing procedures. Recently, alpha stable filters have been used to extract significant features from medical images.
A Feature-based method is introduced for image registration. The feature extraction is based on Bidimensional Empirical Mode Decomposition (BEMD). We have proposed two approach. The first one is a feature selection and reduction method. The registration is performed based on selected features and Bspline interpolation. The second approach is a hierarchically method based on BEMD features. Both methods improved the registration based on intensity of the images, especially for the... 

Gene regulatory modeling in different species is one of the main aims of Bioinformatics. Regarding the limitations of the data available and the perspectives which should be taken into account for modeling such networks, proposed methods up to now have not yet been successful in yielding a comprehensive model. In one of the recent researches, the Gene regulation process is considered as a nonlinear dynamic stochastic process and described by state space equations. Afterwards, in order for the unknown parameters to be estimated, Extended Kalman Filtering is used. In this thesis, first of all, Gene complexes are taken into consideration instead of genes and afterwards, Extended Kalman... 

This thesis presents a novel approach for detection and recognition of multi-view faces whose location is unknown and the illumination conditions are varying. The illumination is a big problem in the face detection and recognition aspects. Two completely different methods are proposed for face detection in this thesis. Our proposed methods do not use the skin colour information for face detection. The detection of faces is accomplished after cancelling the effect of the various illumination conditions. Because of the independency of the approaches to the face’s skin colour, persons with every kind of skin colours are detected even in completely dark environments. Next, the detected faces are... 

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... 

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... 

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... 

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... 

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...