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SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.

Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

Extracting and visualizing physiological parameters using dynamic contrast-enhanced magnetic resonance imaging of the breast

Author(s): P. Armitage, C. Behrenbruch, M. Brady, N. Moore

An analysis procedure is presented that enables the acquisition and visualization of physiologically relevant parameters using dynamic contrast-enhanced magnetic resonance imaging. The first stage of the process involves the use of a signal model that relates the measured magnetic resonance signal to the contrast agent concentration. Since the model requires knowledge of the longitudinal relaxation time T-1, a novel optimization scheme is presented which ensures a reliable measurement. Pharmacokinetic modelling of the observed contrast agent uptake is then performed to obtain physiological parameters relating to microvessel leakage permeability and volume fraction and the assumptions made in the derivation of these parameters are discussed. A simple colour representation is utilized that enables the relevant physiological information to be conveyed to the clinician in a visually efficient and meaningful manner. A second representation, based on vector maps, is also devised and it is demonstrated how this can be used for malignant turnour segmentation. Finally, the procedure is applied to 14 pre- and post-chemotherapy breast cases to demonstrate the clinical value of the technique. In particular, the apparent improved representation of tissue vascularity when compared to conventional methods and the implications for this in treatment assessment are discussed. (c) 2005 Elsevier B.V. All rights reserved.

Full version: Available here

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ISBN: 1361-8415
Publication Year: 2005
Periodical: Medical Image Analysis
Periodical Number: 4
Volume: 9
Pages: 315-329
Author Address: