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June 30, 2011, 01:44:38 PM |
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Got it. Want 0.4btc (or less, you decide) on this address: 16VD78R8nxqJGesE7E9KS6A8TikQQpKNm5
Proof: Random part of the article:
landmarks rather than signal intensity where necessary. However, longitudinal differences in global contrast and geometric distortion are likely to affect both the manual and CBSI measures. We compared our CBSI measures with our manual measures of change. Although we aimed to produce the most precise measures of manual change possible, the adoption of thresholding as an initialisation step could potentially lead to bias in segmentation. Once the threshold-dependent outline was produced, the rater may be lessinclined to change this contour compared with an entirely manual technique. However, we used these thresholds consistently throughout the study on every scan and every contour was manually checked and changed if it was deemed not to follow anatomical boundaries. We applied consistent CBSI parameters (window width and window centre) across the dataset. One limitation of this approach is that the parameter choice for a given subject is dependent on the characteristics of the rest of the study population. However, parameter selection was entirely automated and cohort specific. This automated procedure could be applied to any cohort and would enable this technique to be applicable to new scan acquisitions and different field strengths. Computer-assisted segmentation techniques have shown promise cross-sectionally (for example Iosifescu et al., 1997; Khan et al., 2008), and produce caudate segmentations which have approximately 80% spatial overlap with manually-outlined regions, and similarity coefficients of approximately 90% (Iosifescu et al., 1997). Such techniques may also be of use longitudinally although it is yet to be shown if independent automated segmentations at multiple timepoints can provide sensitive measures of longitudinal volume change. Conclusion While manual measures remain the ‘gold standard’ for caudate volumetry, the development of automated techniques such as the CBSI will become increasingly important as compounds showing promise in model systems of HD require clinical testing in large multi-centre trials. This study has shown the CBSI to be a promising biomarker candidate. However, further va
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