Hi Qiong,

Does FAST produce better results if you skip the normalisation step?

Cheers,

Paul

On 16/07/2019, QU Liangqiong <[log in to unmask]> wrote:
> Hello,
>
> Thank you very much for your illustration.
>
> The pre-processing steps are:
>
> 1. linear registration to MNI space
>
> 2. inhomogeneity correction
>
> 3. skull-stripping
>
> 4. normalization to [0,1]
>
>
> The results are better when adding -N option, but still not quite correct.
>
> See the attachment for an example with the -N option.
>
> [cid:42818c51-0c4d-40f6-916b-c516b8451d29]
>
>
> FAST work well on the original image.
>
> It seems that the image pre-processing steps cause the problem.
>
>
> Thanks very much for your help.
>
>
> Best regards,
>
> Liangqiong
>
> ________________________________
> 发件人: FSL - FMRIB's Software Library <[log in to unmask]> 代表 Taylor Hanayik
> <[log in to unmask]>
> 发送时间: 2019年7月15日 17:41:41
> 收件人: [log in to unmask]
> 主题: Re: [FSL] [FSL] FAST Segmentation problem with all the brain regions are
> classified as GM
>
> Hi,
>
> I’ve had a look at the images you uploaded and they seem to have been
> preprocessed in some way.
>
> Could you describe what processing has already been done to the images prior
> to FAST?
>
> FAST is failing at the bias correction stage. Have you previously bias
> corrected this data before running FAST? If so, you can turn off FAST’s bias
> correction stage by using the -N option.
>
> Also, the data has been scaled to a 0-1 range. Was that step part of some
> preprocessing before FAST?
>
> Could you try running the unprocessed (brain extracted) T1 through FAST to
> see if things work ok?
>
>
>
>
> Cheers,
>
> Taylor Hanayik
>
>
> Taylor Hanayik PhD
> Analysis Research Software Engineer
> FMRIB, John Radcliffe Hospital
> University of Oxford
> [log in to unmask]<mailto:[log in to unmask]>
>
>
>
>
>
> On 9 Jul 2019, at 19:51, QU Liangqiong
> <[log in to unmask]<mailto:[log in to unmask]>> wrote:
>
> Hello,
>
> I have updated two samples of my T1 files (the input to FAST) to
> https://oxfile.ox.ac.uk/oxfile/work/extBox?id=754626B883867C03BB, with name
> S1_7t.nii and S7_3t.nii.
>
> Thank you very much for your help.
>
> Best regards,
> Liangqiong
> ________________________________
> 发件人: FSL - FMRIB's Software Library
> <[log in to unmask]<mailto:[log in to unmask]>> 代表 Taylor Hanayik
> <[log in to unmask]<mailto:[log in to unmask]>>
> 发送时间: 2019年7月10日 2:40:37
> 收件人: [log in to unmask]<mailto:[log in to unmask]>
> 主题: Re: [FSL] FAST Segmentation problem with all the brain regions are
> classified as GM
>
> Hi,
>
> Happy to look into it for you. Could you upload a T1 file (the input that
> you give to FAST)? We’ll have a look and test on our end.
>
> You can upload to Oxford’s file sharing service here:
>
> https://oxfile.ox.ac.uk/oxfile/work/extBox?id=754626B883867C03BB
>
>
> Cheers,
>
> Taylor Hanayik
>
>
> Taylor Hanayik PhD
> Analysis Research Software Engineer
> FMRIB, John Radcliffe Hospital
> University of Oxford
> [log in to unmask]<mailto:[log in to unmask]>
>
>
>
>
>
> On 7 Jul 2019, at 01:41, Liangqiong Qu
> <[log in to unmask]<mailto:[log in to unmask]>> wrote:
>
> Hello!
>
> I want to use “FAST Segmentation” to segment GM/WM/CSF from a skull-stripped
> 3T T1-weighted MR image. But it classifies all the brain regions  as GM. I
> have tuned the parameters, but it still not work.
>
>
> I used the command like “/usr/local/fsl/bin/fast -t 1 -n 3 -H 0.1 -I 4 -l
> 20.0 -o $Output_dir $Input_dir ”
>
>
> I have also tested the same command on some other types of 3T T1-weighted MR
> image, the result seems good.
>
>
> I want to ask:
>
> Is there any requirement of the input of T1-weighted MR image? Why it works
> well on some types of T1-weighted MR image work well, but collapses on other
> types of T1-weighted images.
>
> Could you give me some advice on this?
>
> I am looking forward for your feedback.
>
> Best regards,
> Qiong
>
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