Contents
Tissue-type segmentation and Bias-field (RF-inhomogeneity) correction
- T1-weighted image recommended but not compulsory (image just needs good contrast and SNR)
Initial processing (e.g. reorientation, cropping)
- Brain extraction (and if tissue volumes or cortex is of interest then be very precise here; high accuracy is not so necessary for bias field correction)
- Run FAST (either via the GUI or the command line)
- turn on the option for bias field and restored image (bias-field corrected image)
- Check output:
check the segmentation results by loading either the individual pve images or the pveseg image into FSLView, on top of the original image
- look at the restored image and see if it has removed the bias field
- Troubleshooting:
- try other options (e.g. bias field smoothing, MRF parameter, number of iterations)
- Further analysis:
- Volume of tissues can be obtained by summing the PVE output
Volumetric analysis done in other stats package (e.g. SPSS, Matlab, etc) but for local change analyses look at VBM, vertex analysis, cortical thickness analysis (FreeSurfer), or SIENA/SIENAX
- Alternative:
fsl_anat for bias field correction