Sharif Digital Repository

One of the drawbacks to post-process and to interpret ultrasound medical images is speckle noise. In this paper we used fourth-order partial differential equation method proposed by Lysaker et al. for speckle reduction of ultrasound images. We used two groups of images first was the synthesized noisy image and second is real ultrasonic images. A comparison between our results and to other methods showed that PDE has better SNR and PSNR in most levels of speckle  

Electrical impedance tomography is a simple and economic medical imaging technology which permits regional assessment of the electrical properties of organs within the body based on measurements made from electrodes on the surface of the body. Block method is a new solution for electrical impedance tomography used to enhance image resolution and to improve reconstruction algorithm. Image reconstruction by block method is an ill-posed and nonlinear problem also has memory and time consuming process which can be improved by using modified equations. Improving forward solution for block electrical impedance tomography method can make linear equations for image reconstruction algorithm  

In this paper an Extended Kalman Filter (EKF) has been proposed for the filtering of noisy ECG signals. The method is based on a modified nonlinear dynamic model, previously introduced for the generation of synthetic ECG signals. An automatic parameter selection method has also been suggested, to adapt the model with a vast variety of normal and abnormal ECG signals. The results show that the EKF output is able to track the original ECG signal shape even in the most noisiest epochs of the ECG signal. The proposed method may serve as an efficient filtering procedure for applications such as the noninvasive extraction of fetal cardiac signals from maternal abdominal signals. © 2005 IEEE  

The human being in the environments of modern technology has to endure stresses of many and varied kinds of vibrations. Measuring vibration is an important tool in rehabilitation and biomechanical fields of research. We have proposed image processing as a new method to record and determine the frequency response of human body. The subjects were exposed to whole body periodical vibration while standing on a shaking table. Two digital camcorders were used to capture the motion of colored pencil-dot markers on the skin of human body (forehead) and on the edge of the shaking table. After color spotting each frame, the binary image results were processed using new circle factor criteria proposed... 

In this paper, a Kalman filter technique which is operated in time is introduced for noise reduction on CT set of projections to reconstruct medical images. The experiments were done on medical image of kidneys and the simulated projections are captured by CT scanner. Evaluation results indicated that as the number of projections increase in the collected ray sums corrupted by noise the quality of reconstructed image becomes better in terms of contrast and transparency. However, for the comparison issue, the same conditions are applied for reconstruction of medical image in frequency domain using filter back projection technique. It observes that filter back projection technique does not... 

To enable a relevance feedback paradigm to evolve itself by users' feedback, a reinforcement learning method is proposed. The feature space of the medical images is partitioned into positive and negative hypercubes by the system. Each hypercube constitutes an individual in a genetic algorithm infrastructure. The rules take recombination and mutation operators to make new rules for better exploring the feature space. The effectiveness of the rules is checked by a scoring method by which the ineffective rules will be omitted gradually and the effective ones survive. Our experiments on a set of 10,004 images from the IRMA database show that the proposed approach can better describe the semantic... 

Image registration is an important task in medical image processing. Assuming spatially stationary intensity relation among images, conventional area based algorithms such as CC (Correlation Coefficients) and MI (Mutual Information), show weaker results alongside spatially varying intensity distortion. In this research, a structural representation of images is introduced. It allows us to use simpler similarity metrics in multimodal images which are also robust against the mentioned distortion field. The efficiency of this presentation in non-rigid image registration in the presence of spatial varying distortion field is examined. Experimental results on synthetic and real-world data sets... 

In this article, we look at early, recent, and state-of-the-art methods for registration of medical images using a range of high-performance computing (HPC) architectures including symmetric multiprocessing (SMP), massively multiprocessing (MMP), and architectures with distributed memory (DM), and nonuniform memory access (NUMA). The article is designed to be self-sufficient. We will take the time to define and describe concepts of interest, albeit briefly, in the context of image registration and HPC. We provide an overview of the registration problem and its main components in the section "Registration." Our main focus will be HPC-related aspects, and we will highlight relevant issues as... 

According to the WHO, two individuals die every hour from skin cancer and about 9500 people get skin cancer every day just in the United States. Various computer vision algorithms have been introduced for skin lesion detection, classification, and segmentation. This paper proposes a new segmentation-based algorithm in order to select target components using the persistence diagram of the input images. The results, in comparison with the existing seven different both clustering-and histogram-based segmentation methods using three metrics, show improved performance. Medical image segmentation is an essential task in computer-aided diagnosis. The main improvement of our method is to detect one... 

Spatially-varying intensity noise is a common source of distortion in medical images and is often associated with reduced accuracy in medical image registration. In this paper, we propose two multi-resolution image registration algorithms based on Empirical Mode Decomposition (EMD) that are robust against additive spatially-varying noise. EMD is a multi-resolution tool that decomposes a signal into several principle patterns and residual components. Our first proposed algorithm (LR-EMD) is based on the registration of EMD feature maps from both floating and reference images in various resolutions. In the second algorithm (AFR-EMD), we first extract a single average feature map based on EMD... 

This paper presents a fuzzy approach for contrast enhancement, based on two multi-scale transforms, namely wavelet and contourlet transforms. Separability and nondirectionality of conventional 2D wavelet transform, makes it unsuitable for sparsely representation of curve or line shaped image objects. On the other hand, the contourlet transform is a good alternative for this purpose. In this paper, coefficient enhancement, both in wavelet and contourlet spaces, is carried out by making use of simple fuzzy rules. These rules make the enhancement procedure more understandable and flexible. With this method, the knowledge and experience of the expert from the distribution of the coefficients can... 

Medical images include information about human body which are used for different purposes such as surgical and diagnostic plans. Compression of medical images is used in some applications such as profiling patient's data and transmission systems. Regard to importance of medical images information, lossless or near-lossless compression is preferred. Lossless JPEG, JPEG-LS and lossless version of JPEG2000 are few well-known methods for lossless compression. JPEG2000 is one of the latest and provides good compression ratio, however, it is complex [1]. In real time application which needs hardware implementation, low complex algorithm accelerates compression process. In this paper, a lossless... 

Medical images contain information about vital organic tissues inside of human body and are widely used for diagnoses of disease or for surgical purposes. Due to vital rule of image reconstruction in medical sciences the corresponding algorithms with better efficiency and higher speed is desirable. Most algorithms in image reconstruction are operated on frequency domain such as filtered back projection. In this paper, a Kalman filter technique which is operated in time domain is introduced for reconstruction of CT medical images. Results indicated that as the number of projection increases in both normal collected ray sum and the collected ray sum corrupted by noise the quality of...