Sharif Digital Repository

The fast-growing development of engineering and medical sciences leads to the diagnosis and treatment of diseases with higher accuracy and in the early stages of the disease. Medical imaging systems are considered as a crucial and effective tool in this field that based on the principle of technology used, are able to image various tissues with high quality. In recent years, photoacoustic imaging has attracted the attention of many researchers and engineers, because it able to image different tissues with good resolution and penetration depth non-invasively and without the use of ionizing radiation. The photoacoustic system response is a low-pass filter that passes only low-frequency... 

Thesedays, personnel surveillance at security checkpoints, such as airports, is becoming increasingly important. Improvements in various fields of imaging techniques provided an attractive opportunity for automatic personnel servaillance at high security checkpoints. Millimeter-wave imaging systems are capable of penetrating through clothes and thin layers to form an image of a person with very high resolution and without no health hazard at moderate power levels. Therefore millimeter-wave imaging is becoming an important method for surveillance purposes. Typically, there are two common methods for microwave imaging, including synthetic aperture imaging and phased-array imaging. Synthetic... 

Compton imaging is an imaging technique in which Compton scattering is used to produce images from a gamma-ray source. Compton imaging systems are also known as Compton cameras. The basic design of Compton imaging systems consists of two-position detectors that are sensitive to the position and energy scattered from gamma rays. The gamma rays collide with the Compton scatterer detector and the scattered photons are absorbed in the absorber detector. Compton imaging performs well the ground radiation during the scattering processes through the separation of energy. The quality of images produced by Compton imaging depends on a variety of factors including detector energy resolution,... 

In recent years, optical biomedical imaging techniques show great potential in noninvasive imaging. Although these methods have many advantages over other biomedical imaging methods (such as Computerized Tomography (CT), Magnetic Resonance Imaging (MRI) and etc.), these techniques confront with some problems such as optical scattering, light absorption and etc. For in vivo imaging, the short-wavelength infrared region (SWIR; 1,000–2,000 nm) provides several advantages over the visible and near-infrared regions: general lack of auto-fluorescence, low light absorption by blood and tissue, and reduced scattering. In this thesis we want to analyze the traditional IR imaging techniques and... 

Acoustic-resolution photoacoustic microscopy (AR-PAM) system can provide 3-D images of facial tissues. The lateral resolution of AR-PAM depends on the numerical aperture (NA) of the acoustic lens and the central frequency of the ultrasonic transducer. There is a trade-off between resolution enhancement and imaging depth. The acoustic beam is tight in the acoustic focal plane but expands in the out-of-focus regions, deteriorating the resolution. High-NA AR-PAM has depth-variant resolution. Synthetic aperture focusing technique (SAFT) based on a virtual detector (VD) concept can compensate for the beam shape and improve the lateral resolution via beamforming. Although, beamforming can enhance... 

3D reconstruction of digital images is one of the sub- branches of computer vision which is used in various fields such as computer graphics, compute animation, etc. in general, two approaches exist for solving 3D structure problem. In the first approach to obtain the model, we need a certain distance of the whole object level at a certain point and to do so, a sensor is used which is directly interacting with the object. For instance, we use lasers and estimate the depth using that depth to make 3 D model. In the second approach we use the images we have at different instaces of an object (sensor is the camera that is sensitive to light). Using these data and the machine learning... 

Medical ultrasound imaging is one of the common imaging methods in modern medicine, which is used to diagnose and even treat some diseases due to its cheapness and harmlessness. Medical ultrasound transducer arrays have a significant error rate. They are a major cause of failure in ultrasound imaging systems. This problem causes a noticeable decrease in the quality of the images and medical misdiagnoses. The topics of accurate detection of the location and severity of the error or failure, as well as the compensation for weak transducers by signal processing methods, have received less attention from predecessor researchers. In this thesis, an innovative method for accurate error detection... 

Digital analysis of reservoir rocks prepares a powerful tool in the field of porous media studies and provides appropriate information of single / multiphase flows by performing numerical simulations on porous media images. In order to access the necessary tools to benefit from digital rock analysis and characterization, we need accessing the porous media images, the geometric distribution and the spatial distribution of pores and grains through imaging or reconstruction methods. Porous media reconstruction methods are known as an alternative to imaging techniques. In addition, reconstruction methods have the ability to fix problems and imperfections associated with imaging, such as... 

3D-object modeling and its representation in computers are one of the interested fields in computer science and engineering and problems like object and environment modeling, representation, storage and physical interactions are some of the important problems in this field. Increasing the applications of the technologies like localization, machine vision and virtual reality made the 3D-object modeling and its related problems, like 3D-model extraction and reconstruction, a nowadays interested challenges and a variety of solutions such as time of flight sensors,
structured light, sonar sensors and multi-camera reconstruction are presented for it. Multi-camera solutions, just like the... 

Nowadays, medical imaging has become one of the most important tools in medical sciences, which helps doctors in the field of diagnosis. The most common imaging methods include X-ray CT scan imaging, MRI, and ultrasound imaging, each of which has its own unique advantages and limitations. One of the main advantages of ultrasound imaging is the use of low-risk, non-ionizing acoustic waves for imaging, and also ultrasound imaging methods work better than X-ray imaging for soft tissue imaging. Ultrasound imaging systems can be divided into two main categories, reflection imaging and transmission imaging structures, where reflection structures are mostly used to detect surface characteristics,... 

Recently Infrared imaging has been very much considered for its applications.and because the infrared wavelengths are harmless, considered in medical and industrial applications. the imaging system examined in this thesis is passive and the object's own radiation is received by a single-pixel detector, these images are taken by two superconducting sensors and a pyroelectric Sensor. the purpose of this thesis is to improve the quality of images And reconstruction for the resulting images and if possible, optimize the system. to improve this system, various work has been proposed and done. including parabolic mirror distortion survey available in the system and compensated for it, take a... 

In this thesis its considered the characterization of an ultrasound wave in a medium with some obstacles. Derivation of speed of molecules and pressure of the wave is carried out in the Cartesian coordinates system. Simulation is carried out to prove the dependency of wave speed to set up parameters such as the target point (x,y,z) at which the speed value is obtained, the location of the obstacles, the amplitude of original wave emitting from the source, and the propagation speed in different layers of the medium. From the numerical results, it is apparent that the amplitude of the speed wave gets degraded as the wave travels through the medium which is a function of reflection and... 

Medical imaging is an indispensable component of modern medical research as well as clinical practice. However, Magnetic resonance Imaging and Computational tomography are expensive, and it is difficult to be used in many scenarios worldwide. As such, many parts of the world still do not have sufficient accessibility to these techniques. To make medical devices more accessible, affordable and efficient, it is crucial to reflect upon our current imaging paradigm for smarter imaging. According to Compressed Sensing theory, if there is information other than the signal bandwidth value, such as the being sparse in a suitable domain, nonlinear optimization methods can be used to accurately... 

e study of the brain’s neural activity is an active research area in computational neuroscience aiming to provide insights about the functionality of the brain as well as dysfunctions that underlie disorders. Functional Magnetic Resonance Imaging (fMRI) plays an important role in brain studies by providing non-invasive records of neural activities during a specific task with location sensitivity. Recent advances in statistics and machine learning offer powerful tools for paern recognition and processing of fMRI data. In this thesis, we decode information recorded via fMRI from the visual cortex to reconstruct images presented to subjects. Current reconstruction methods face numerous... 

Nowadays millions of images are shared on social media every day , So image inpainting has become an important issue . After advent of Generative adversarial network image inpainting methodes based on deep learning has been revived and significant progress has been made . For a proper image inpainting , The inpainted image must benefit from the appropriate structure and texture in the missing regions . Therefore, in this project , an attempt is made to use a two-stage structure by using Generative adversarial network .in first stage first by using Gabor filters , the image structure is extracted and then the image structure is completed , while the second stage focuses only on the... 

Sparse-view computed tomography (CT) is recently proposed as a promising method to speed up data acquisition and alleviate the issue of CT high-dose delivery to patients. However, traditional reconstruction algorithms are time-consuming and suffer from image degradation when faced with sparse-view data. To address this problem, we propose two new frameworks based on deep learning (DL) that can quickly produce high-quality CT images from sparsely sampled projections and is able for clinical use. Our first DL-based proposed model is based on the convolution, and residual neural networks in a parallel manner, named the parallel residual neural network (PARS-Net). Besides, our proposed PARS-Net... 

Nowadays, millimeter-wave imaging is widely used in security and medical applications. The growing threat from terrorist attacks is driven research on novel ways to enhance security inspection systems. Millimeter-wave imaging not only is an effective option of penetrating into dielectric materials including cloth, but also provides suitable imaging resolution. Moreover, millimeter-wave imaging is capable of identifying different materials making it a promising option for concealed weapon detection. In spite of X-ray, millimeter-wave imaging is non-ionizing, allowing for non-invasive imaging. In this thesis, first we investigate different millimeter-wave imaging systems and reconstruction... 

Sight is probably our most important sense. Every day, humans are exposed to many visual stimuli in their surroundings. The human brain is able to identify and prioritize important and valuable stimuli and memorize them. Identifying and remembering these valuable stimuli is vital to meeting the needs and maintaining survival. The aim of the proposed research is to find the effect of reward learning on the coding of visual objects in the human brain. Previous results have shown that long-term reward-object association make valuable objects more recognizable behaviorally. Studies have also shown that visual stimuli and the pattern of activity of primary visual cortex neurons are closely...