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In this paper, we present a novel framework to segment and quantify stenosed coronary arteries in 3D contrast enhanced computed tomography angiography (CTA). According to our knowledge, no commercially available software package permits fully automated detection and assessment of atherosclerotic stenosis. Therefore, in clinical practice, the radiologist has to make a detailed evaluation, segment by...
This paper presents the classification of benign and malignant breast tumor based on fine needle aspiration cytology (FNAC) and probabilistic neural network (PNN). Five hundred and sixty nine sets of cell nuclei characteristics obtained by applying image analysis techniques to microscopic slides of FNAC samples of breast biopsy have been used in this study. These data were obtained from the University...
A hybrid lossy image compression technique using classified vector quantiser and singular value decomposition is presented for the efficient representation of medical magnetic resonance-brain images. The proposed method is called hybrid classified vector quantisation. It involves a simple yet efficient classifier based gradient method in the spatial domain which employs only one threshold to determine...
In the past years, much research has been done about ocular hemodynamics using fluorescein angiography. One of the most promising parameters is the transit time of retinal blood flow, which tries to determining how long a dye takes in reach, fills out and leaves the human retina. To achieve this, both individual angiograms and sets of them have to be analyzed. In order to perform this analysis in...
In many image-processing applications it is necessary to register multiple images of the same scene acquired by different sensors, or images taken by the same sensor but at different times. Mathematical modeling techniques are used to correct the geometric errors like translation, scaling and rotation of the input image to that of the reference image, so that these images can be used in various applications...
A technique is proposed for detection of tumor in digital mammography. We here proposed a statistical parameters such as probability and entropy based image segmentation of mammographic images. This algorithm is consists of three stages. First we compute probability of each quantization level of the image and replace every pixel by its probability to generate probability image. On this image we perform...
In today's world, increasing life expectation have made the heart failures of important concern. For clinical diagnosis, parameters for the condition of heart are needed. Accurate and fast image segmentation algorithms are of paramount importance prior to the calculation of these parameters. An automatic method for segmenting the cardiac magnetic resonance (CMR) images is always desired to increase...
Medical image fusion has been used to derive the useful information from multi modal medical images. The proposed methodology introduces evolutionary approaches for robust and automatic extraction of information from different modality images. This evolutionary fusion strategy implements multiresolution decomposition of the input images using wavelet transform. It is because, the analysis of input...
In this paper, we present an intelligent approach to analysing prostrate ultrasound images in order to diagnose prostate cancer. Algorithms based on fuzzy image processing are applied first to enhance the contrast of the original image, to extract the region of interest and to enhance the edges surrounding that region. Then, we extract features characterising the underlying texture of the regions...
Artificial neural networks are significantly used in the field of ophthalmology for accurate disease identification which further aids in treatment planning. In this paper, an automated system based on Self-Organizing neural network (Kohonen network) is proposed for eye disease classification. Abnormal retinal images from four different classes namely non-proliferative diabetic retinopathy (NPDR),...
We propose a new ultrasonic image analysis system that can be utilized as an effective tool in classifying liver states as normal, hepatitis, or liver cirrhosis. In this system, we first define suitable settings for the ultrasonic device, then remove the inhomogeneous structures from the area of interest in the image, and then, by using the forward sequential search method, look for the useful texture...
This paper addresses a novel issue of intuitionistic fuzzy c means color clustering using intuitionistic fuzzy set theory. The intuitionistic fuzzy set theory takes into the membership degree and non membership degree. Non membership degree is calculated from Sugeno type intuitionistic fuzzy complement. The introduction of another uncertainty term i.e. the non membership degree helps to converge the...
Medical image compression techniques should give high compression ratios apart from preserving vital information in medical images. In this paper we propose a compression technique for four-dimensional functional Magnetic Resonance Images (fMRI). The proposed technique uses bandelet transform to capture the anisotropic regularity of edge structures apart from capturing regularity information from...
Medical images like mammograms are very difficult to analyze because of their low contrast. Different fractal features are used for analyzing mammograms in this paper. The new fractal feature derived from the modified average image is found to be a better feature for distinguishing between normal, malignant, benign and mammograms with microcalcifications. The study is performed on the mammograms obtained...
It is well known that the human visual system (HVS) cannot sense all changes in an image/video due to its underlying physiological and psychological mechanisms. We propose a complete masking estimation model for image/video in this paper. In our model, a very important mechanism of the HVS, visual attention, is incorporated to the existing just noticeable difference (JND) estimation models. A formula...
Three-dimensional reconstruction of cryo-electron tomography (cryo-ET) has emerged as the leading technique in analyzing structures of complex pleomorphic cellulars. A classical iterative method, simultaneous algebraic reconstruction technique (SART), has been employed to reconstruct volume images in cryo-ET. However, SART starts with an arbitrary approximation and takes into account only a weighted...
Contralateral subtraction (C-sub) is a computer-aided diagnosis technique for detecting pulmonary nodules in chest radiographs. This technique enhances nodules in a chest image by subtracting its right / left reversed mirror image from the original image. In this paper we propose an improved C-sub scheme, which uses a ribcage boundary detection method and a global matching method newly proposed in...
Ultrasound images contain speckle noise that creates granular pattern which degrades their quality. Typically, the granular noise has a circular pattern that circles the position of the ultrasound probe which acts as it center. As such, anisotropic diffusion filter cannot completely remove the granular noise. In this work, we propose a technique that pre-processes an ultrasound image using warping...
In chemoembolization, chemotherapy drugs and thrombotic agents are directly injected into the liver tumor through a catheter navigated to the artery that supplies the tumor. In order to help surgeons to train their hand-eye coordination skills to reduce the risk of injecting the thrombotic agents incorrectly and deprive normal tissue of its blood supply, this paper proposes a method for rendering...
Pulmonary radiographs are essential tools to the evaluation and diagnosis of suspected infections of the lower respiratory system. Interpretation of a radiograph in the clinical context is a valuable diagnostic adjunct to the selection and the management of a specific clinical protocol for therapy. The key element in the proper diagnosis of a bacterial pulmonary infection is the analysis of the radiographic...
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