Dear Sam,
Firstly, this kind of registration will be quite difficult, so you probably have to try several approaches in order to find one that works well.
Secondly, if you are not using the mutual information cost function (or normalised mutual information) then switch to that, as this is crucial for CT to MRI registration.
Thirdly, are you brain extracting both images? If not, then do this as the non-brain structures in the CT are so prominent that they are likely to be causing major problems.
Lastly, your approach sounds fine (given the above). You may need a very large up-weighting on your ventricle mask in order for it to have an effective (e.g., values of 100 or 1000) but the principle is sound. Alternatively, if you want to specify individual point landmarks then you might find that the pointflirt tool is more useful for you.
All the best,
Mark
> On 20 Jun 2017, at 05:45, Sam Choi <[log in to unmask]> wrote:
>
> Dear FSLers,
>
> I am working with CT scans of stroke patients and would like to register the brains and stroke lesions in CT space into MNI space. Currently, the registration methods I have been trying have not been working well. The registered lesions often overlap the ventricles in the MNI template.
>
> A suggestion that I received is to try manual registration. Specifically, I would select certain areas/landmarks around the ventricles in the CT scan and register these areas to the MNI template. The expectation of this manual registration process is to improve registration around the ventricles such that the stroke lesions do not overlap the ventricles in the MNI template.
>
> With this in mind, how do I perform manual registration using FSL tools? Would the following steps make sense:
> 1) Using the CT scan, create a mask of the areas/landmarks around the ventricles that I want to improve registration (for brevity, I will refer to this as the "ventricle mask" herein).
>
> 2) Given that I am dealing with stroke patients, I also need to create an inverted lesion mask such that FLIRT ignores the lesion areas during registration (i.e., lesion areas are weighted 0, whereas rest of brain is weighted 1).
>
> 3) Use FSLMATHS to add the ventricle mask and the inverted lesion mask together. The resulting mask file would lead to the lesion areas still having a weight of 0, while the regions part of the ventricle mask will have a weight >1.
>
> 4) Use FLIRT to register the CT scan to the MNI template. Use the -inweight option to input the mask created from Step 3 (above).
>
> I would appreciate any insight you may have.
> Thanks for your help!
>
> Sam
|