When multiple scanners are used to acquire diffusion MR image data from the same patient (even on the same day), there is no guarantee that identical settings will result in comparable images of a specific organ and region. Despite this, for clinical use, any software developed to compute the apparent diffusion coefficient (ADC) must be expected to give equivalent results. What is needed is a phantom study with appropriate design which supports a calibration, so that appropriate settings for equivalent diffusion measurements can be defined among different scanners. Ideally the calibration process needs to be fully automatic, so that it can be used by non-experts in a clinical setting. We intend to developed software which automatically locates five cylinders in an ice water phantom (designed for the QuIC-ConCePT project) and then measures the different diffusion values in the cylinders. The location algorithm uses an object recognition process which culminates in robust Likelihood estimation of position and orientation, computed using probabilistic Hough Transforms. This process estimates cylinder locations to an accuracy of a few pixels, even in the presence of field inhomogeneity and significant spatial distortion. Our assessment of performance includes quantification of possible errors due to; data inaccuracy, distortion due to poor shimming, signal to noise, field inhomogeneity and image clutter (i.e. ice). Results indicate that reliable localisation can be obtained using these methods for realistic clinical settings.
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