Hi Krish, I'll be brave and answer this one - since I've asked the same questions myself in the past... 1) As I understand it, the bias field estimations and segmentation procedure run iteratively together, so you can't have one without the other. 2) Yes, but you need to output a dilated version of the bias field (-oba option) and then run avwmaths_32R (i.e. need to have floating point data). You can revert back to more sensibly sized bit depths after you've multiplied by the bias field so: fast -l 100 -i 8 -oba 100 <betted_input_image> avwmaths_32R <input_image> <betted_input_image>_abias <output_image> Cheers, Clare ___________________________________________________ Clare E. Mackay, Ph.D. Research Fellow, Prince of Wales International Research Centre (POWIC), University Department of Psychiatry, Warneford Hospital, Oxford. OX3 7JX. UK tel: 01865 455910 fax: 01865 455922 OCMR: 01865 221866 / 72 [log in to unmask] www.psychiatry.ox.ac.uk/powic ___________________________________________________ >>> [log in to unmask] 01-06-2004 13:00:59 >>> Hi, We have just started generating mp-rage volume scans from our new 3T Siemens Trio, using the 8-channel head coil. The images look great, with excellent grey-white matter contrast, but there is a noticeable bias field. Fast seems to make a great job of bias-correcting these images, but I have two questions: 1) I wonder whether it is possible (on the command line) to simply bias-correct the images, without doing the segmentation? Or does the segmentation not really contribute to the processing time? 2) Is it possible to apply the generated bias field image to another image (i.e. The non-skullstripped image)? Is it simply a matter of multiplying in avwmaths? Thanks and all the best, Krish -- Dr K.D. Singh Senior Lecturer and Convenor of the Neuroimaging Research Group, Director, MRI Research Centre, Neurosciences Research Institute Aston University, Birmingham B4 7ET, U.K. Tel/Fax: +44 (0)121 [359 3611 ext 5176/5190]/[333 4220] [log in to unmask], http://www.aston.ac.uk/lhs/staff/singhkd/