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Estimating white matter ber pathways from a diffusion tensor MRI dataset has many important applications in medical research. Even after the definition of white matter ROIs, the precise selection of appropriate fibers of interest for further analysis in population studies is often a time consuming and error prone task. Tractography segmentation methods based on pairwise distances between fibers are...
In this paper we propose an alternative method to estimate and visualize the strain rate tensor (ST) in magnetic resonance images (MRI) when phase contrast MRI (PCMRI) and tagged MRI (TMRI) are not available. This alternative is based on image processing techniques. Concretely, an elastic image registration algorithm is used to estimate the movement of the myocardium at each point. Our experiments...
This paper presents an analysis method for ultrasound images based on modeling the speckle noise with a Rayleigh distribution. This distribution is parametrized by the parameter sigma, related to the characteristics of the biological tissue. Since some parameters of the Rayleigh distribution are proportional to the value of sigma, the local estimation of such statistics allows the identification of...
A method to identify different tissues in ultrasound images is presented. Assuming a Rayleigh model for speckle, the different tissues present in the image will be related to the Rayleigh sigma parameter, with different values for each different tissue. The parameter is locally estimated using well known estimation methods for the Rayleigh distribution, such as the maximum likelihood estimator. A...
A new and complementary method to assess image quality is presented. It is based on the comparison of the local variance distribution of two images. This new quality index is better suited to assess the non-stationarity of images, therefore it explicitly focuses on the image structure. We show that this new index outperforms other methods for the assessment of image quality in medical images
In this paper, we present a segmentation method for the hip joint from 3D ultrasound data. The proposed approach starts from a well-known energy formulation of the segmentation problem, and employs the extended local structure tensor as image feature in order to incorporate gray level and texture information in a common framework. Using the Kullback-Leibler distance as an intrinsic dissimilarity measure,...
A segmentation application prototype of the volume of the left ventricle for Magnetic Resonance Imaging is being developed. The foundation for this work is given by modeling possible radial deformations of the epicardium and endocardium contours by means of a Markov Random Field over which the most probable configuration is estimated. The field makes use of a Bayesian approach based on a priori terms...
Automatic detection of microcalcifications in mammograms constitutes a helpful tool in breast cancer diagnosis. Radiologist's confidence level on microcalcification detection would be improved if a probability estimate of its presence could be obtained from computer-aided diagnosis. In this paper we explore detection performance of a simple Bayesian classifier based on Gaussian mixture probability...
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