On Sun, 6 Jan 2019 20:18:40 +0100, Matthieu Vanhoutte <[log in to unmask]> wrote:
>Could you answer to my previous question ?
These quality paremeters evaluate the data _before_ preprocessing, thus there is no way to influence these parameters retrospectively:
Copy and paste from the CAT12 manual:
If you have loaded quality measures, you can also display the Mahalanobis distance between two measures: mean correlation and weighted overall image quality. These two are the most important measures for assessing image quality. Mean correlation measures the homogeneity of your data used for statistical analysis and is therefore a measure of image quality _after_ pre-processing. Data that deviate from your sample increase variance and therefore minimize effect size and statistical power. The weighted overall image quality, on the other hand, combines measurements of noise and spatial resolution of the images _before_ pre-processing. Although CAT12 uses effective noise-reduction approaches (e.g. spatial adaptive non-local means filter) pre-processed images are also affected and should be checked.
>> Le 23 déc. 2018 à 22:00, Matthieu Vanhoutte <[log in to unmask]> a écrit :
>> Dear CAT12’s experts,
>> Is there a way to tune parameters in CAT12’s segmentation & surface extraction process in order to improve resolution, noise and bias scores ?
>> I ran this in on T1 subject and only got these scores:
>> resolution: 83.58% (B)
>> noise: 80.06% (B-)
>> bias: 78.44% (C+)
>> IQR: 81.38 (B-)