<> = Tissue-type segmentation and Bias-field (RF-inhomogeneity) correction = * T1-weighted image recommended but not compulsory (image just needs good contrast and SNR) * [[InitialProcessing|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