• Fast
• StepByStep

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