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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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