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Understanding the connectome of the human brain is a major challenge in neuroscience. Discovering the wiring and the major cables of the brain is essential for a better understanding of brain function. Diffusion Tensor imaging (DTI) provides the potential way of exploring the organization of white matter fiber tracts in human subjects in a non-invasive way. However, it is a long way from the approximately...
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...
Automatic cell segmentation and dead cell detection in microscopic images play a very important role in the study of the behaviour of lymphocytes. In this paper, a distance and watershed transforms based cell segmentation algorithm has been proposed to segment cells by using CFSE image, and a dead cell detection algorithm is also proposed to detect cell dead event. Experimental results have shown...
Motivated by the need of information integration from different image modalities for treatment of ocular diseases, this paper introduces an algorithm that registers image pairs from a complete IndoCyanine green angiography (ICG),containing Infra-Red (IR) and ICG images, for diagnosis of diseases in the choroidal layer, such as exudative senile macular degeneration. Challenges of the work include low...
Template matching is used for many applications in image processing. Cross correlation is the basic statistical approach to image registration. It is used for template matching or pattern recognition. Template can be considered a sub-image from the reference image, and the image can be considered as a sensed image. The objective is to establish the correspondence between the reference image and sensed...
Registration is the process of finding transformations that makes correspondence between related image pairs so that pixels in the two images precisely coincide to the same points in the scene. Once registered, the image can be combined or fused in a way that improves useful information extraction. The log-polar transform (LPT) is a well known space variant image registration scheme used for medical...
Many medical image segmentation techniques have been proposed by lots of authors but they are mainly dedicated to particular solutions. There is no generic method for solving the image segmentation problem. The difficulty comes from that two types of noise are presented in medical images: physical noise due to the acquisition system, for example, Optical, X-rays and MRI, and physiological noise due...
In clinical Magnetic Resonance Imaging (MRI), any reduction in scan time offers a number of potential benefits ranging from high-temporal-rate observation of physiological processes to improvements in patient comfort. In this paper we proposed a reconstruction algorithm by applying contourlet thresholding in inverse scale space flows. We improved the inverse scale space with the noise item in which...
In this paper, a scheme using fuzzy mathematical morphology operations is proposed for extracting coronary arteries tree on angiogram. After the enhancement of image with the traditional morphological top-hat operator, the vessel image is filtered with the fuzzy morphological opening with a set of linear structuring elements at different orientation. At the same time, the enhanced image is also filtered...
Nowadays, the transmission of digitized medical information has become very convenient due to the generality of Internet. Internet has created the biggest benefit to achieve the transmission of patient information efficiently. However, it is easier that the hackers can grab or duplicate the digitized information on the Internet. This will cause the following problems of medical security and copyright...
Angiogenesis, a rigorously regulated process by which new blood vessels are formed, occurs under both physiological and pathological conditions, especially under tumor development. How to accurately quantify vessels in experimental models from angiogenesis assay is of great importance for assessing the angiogenic activity of drugs or chemical compounds. Currently, objective quantification of new vascular...
Although functional magnetic resonance imaging (fMRI) data are acquired as complex-valued images, traditionally most fMRI studies only use the magnitude of the data. FMRI analysis in the complex domain promises to provide more statistically significant information; however, the noisy nature of the phase poses a challenge for successful study of fMRI by complex-valued signal processing algorithms....
Automatic mammogram analysis is important in early breast cancer detection. In this paper, we present a multi-resolution approach to automated classification of mammograms using Gabor filters. Specifically, Gabor filters of different frequencies and orientations have been used to extract textual patterns of mammograms. To increase classification efficiency and reduce feature space, statistic t-test...
Recent developments in medical imaging technology have enabled us to acquire high-resolution datasets within a few minutes. It is important for a physician to recognize three-dimensional structure of vessels prior to any vascular treatments. However, extracting this structure is not a simple image processing task. In this paper, we propose an algorithm to extract hepatic artery from CT datasets through...
Skeleton has very important applications in objects expression, data compression, computer vision and animation. In the discrete space, the basic skeleton algorithms have two categories: one is thinning, the other is based on the distance transformation, in a high-dimensional space generated from the surface to form the ridge to create a skeleton. The skeleton which is based on the distance transform...
Medical image recognition is crucial step of medical image processing and has become a very hot research topic. But many problems, which are caused by a great deal of missing, polluting, and superimposing of the signals, still generally exist in practical application, such as the low recognizing rate. How to recognize the useful signals from badly polluted images has become a difficult point in medical...
Persistent infections with carcinogenic human Papillomavirus (HPV) are a necessary cause for cervical cancer, which is the fifth most deadly cancer for women worldwide. Approximately 20 million Americans are currently infected with HPV but only a subset will develop cervical cancer. While a negative HPV test indicates a very low risk for cervical cancer, a positive test cannot discriminate between...
Endothelial permeability is associated with the genesis and development of atherosclerosis. Computerized image analysis is utilized to investigate the relationship between endothelial permeability and endothelial morphology. First, microscopic images are segmented to detect endothelial cells using the speckle reduction anisotropic diffusion and marker-controlled watershed, whose optimal parameter...
Image retrieval from distributed database is one of the challenging tasks in recent researches. Unlike text retrieval through SQL, MYSQL, etc, image retrieval is not an easy task because of its storage space, color, shape and texture factor. We propose a technique of retrieving images from a distributed database environment by giving a region of an image as an input query. By applying segmentation...
We propose an efficient, deterministic algorithm designed to reconstruct images from real Radon-transform and attenuated Radon-transform data. Its input consists in a small family of recorded signals, each sampling the same composite photon or positron emission scene over a non-Gaussian, noisy channel. The reconstruction is performed by combining a novel numerical implementation of an analytical inversion...
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