Kevin Robinson

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OBJECTIVE The purpose of this article is to determine the feasibility of using computer-assisted diagnosis (CAD) techniques to automatically identify, localize, and measure body fat tissue from a rapid whole-body MRI examination. CONCLUSION Whole-body MRI in conjunction with CAD allows a fast, automatic, and accurate approach to body fat measurement and(More)
Frequently MRI data is characterised by a relatively low signal to noise ratio (SNR) or contrast to noise ratio (CNR). When developing automated Computer Assisted Diagnostic (CAD) techniques the errors introduced by the image noise are not acceptable. Thus, to limit these errors, a solution is to filter the data in order to increase the SNR. More(More)
As whole body MRI (WB-MRI) gains currency, the data this class of technique generates presents new challenges for the imaging community. One acquisition protocol currently being applied with considerable success entails imaging the subject in a number of successive coronal sections, resulting in a high resolution, gap free, full body acquisition. However(More)
In recent years non-invasive medical diagnostic techniques have been used widely in medical investigations. Among the various imaging modalities available, Magnetic Resonance Imaging is very attractive as it produces multi-slice images where the contrast between various types of body tissues such as muscle, ligaments and fat is well defined. The aim of this(More)
We present a morphological approach to the reconstruction of fine branching structures in three dimensional data, developed from the basic procedures of reconstruction by dilation. We address a number of closely related questions arising from this reconstruction goal, including issues of struc-turing element size and shape, noise propagation, iterated(More)
A comparison paper is presented to evaluate the results from five smoothing filters. The filters are linear, nonlinear isotropic and nonlinear anisotropic designed to smooth homogeneous areas while preserving the higher moments in the data. The methods are outlined and then evaluated on the extent to which edge information is preserved and unwanted noise is(More)