Matthew D. Blackledge

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We describe our semi-automatic segmentation of whole-body diffusion-weighted MRI (WBDWI) using a Markov random field (MRF) model to derive tumor total diffusion volume (tDV) and associated global apparent diffusion coefficient (gADC); and demonstrate the feasibility of using these indices for assessing tumor burden and response to treatment in patients with(More)
OBJECTIVE To compare geometric distortion, signal-to-noise ratio (SNR), apparent diffusion coefficient (ADC), efficacy of fat suppression and presence of artefact between monopolar (Stejskal and Tanner) and bipolar (twice-refocused, eddy-current-compensating) diffusion-weighted imaging (DWI) sequences in the abdomen and pelvis. MATERIALS AND METHODS A(More)
We present pyOsiriX, a plugin built for the already popular dicom viewer OsiriX that provides users the ability to extend the functionality of OsiriX through simple Python scripts. This approach allows users to integrate the many cutting-edge scientific/image-processing libraries created for Python into a powerful DICOM visualisation package that is(More)
PURPOSE To introduce T2-adjusted computed DWI (T2-cDWI), a method that provides synthetic images at arbitrary b-values and echo times (TEs) that improve tissue contrast by removing or increasing T2 contrast in diffusion-weighted images. MATERIALS AND METHODS In addition to the standard DWI acquisition protocol T2-weighted echo-planar images at multiple(More)
Quantitative whole-body diffusion-weighted MRI (WB-DWI) is now possible using semi-automatic segmentation techniques. The method enables whole-body estimates of global Apparent Diffusion Coefficient (gADC) and total Diffusion Volume (tDV), both of which have demonstrated considerable utility for assessing treatment response in patients with bone metastases(More)
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