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Hi Everyone, I was at the latest FSL course in Montreal last month (thanks so much for the great course!) and I was just reviewing the slides on BET2. There is a slide on page 57 of the booklet which mentions BET2 "subsequently fits inner skull, outer skull and outer scalp using T1- and T2- weighted images." This leads me to ask a couple questions: 1. I actually didn't collect a T2-weighted structural scan, but I think FSL is performing BET as it should (see below). Should I be concerned that I don't have a T2-weighted scan? How does BET2 work without the T2-weighted scan? 2. In the future, if I was to collect a T2-weighted scan, how can I tell FSL which image file to use? Currently, I cannot find a way to link another input file in the BET GUI. Also, I've been having problems with BET either leaving too many pieces of non-brain, or taking big pieces of brain out....very hard to find the sweet spot with BET, and this changes with each brain I analyze. On page 56 of the booklet you show an example where "leaving small pieces of non-brain is unimportant for most apps". Could you please describe why this is? If I'm registering functional data to this T1 brain and also registering this T1 brain to the MNI standard, wouldn't any extra pieces, or brain deformities cause problems? Oh, and also could you possibly give an example of a tolerable amount of non-brain pieces? In the picture in the booklet you have 2 small pieces, but I'm having problems getting it down to such a small amount without taking big chunks out...so how much is too much? :) Thanks so much for your help! Have a great day, Dar