Hi,
Few naive questions about the Rigid registration with MI dialog box, what are the reference_threshold, source_threshold, reference_reduction_factor and error_Epsilon parameters referring to? I manage to co-register preclinical images with this tool but it takes ages to compute... I was wondering if altering the default values for these parameters might help? but to do so, I'd like to understand what they are for...
Cheers,
Rv
Rigid registration with MI dialog box
Rigid registration with MI dialog box
__________________________________
Hervé BOUTIN, PhD
Senior Research Scientist
University of Manchester
Faculty of Biology, Medicine and Health
email: herve.boutin@manchester.ac.uk
__________________________________
Hervé BOUTIN, PhD
Senior Research Scientist
University of Manchester
Faculty of Biology, Medicine and Health
email: herve.boutin@manchester.ac.uk
__________________________________
Re: Rigid registration with MI dialog box
Hi,
You could find some information on this part of documentation (Aims command line):
http://brainvisa.info/doc/aimsdata-4.3/ ... 08s02.html
In fact, Brainvisa interfaces the AimsMIRregister command line, which is usable in a terminal too.
If you launch : AimsMIRegister -h, you will get some information about options.
When a command is interfaced by BrainVISA, some options can be hidden to make easier to use.
Here the link between brainvisa and command line names :
"reference_threshold" = [ --threshref | --seuilref <FLOAT> ] : relative thresh applied prior to grav cent estimation
"source_threshold" = [ --threshtest | --seuiltest <FLOAT> ] : relative thresh applied prior to grav cent estimation
"reference_reduction_factor" = [ --refstartpyr <S32> ] level of the multiresolution optimization: start resolution level for ref
"error_Epsilon" = [ --error <FLOAT> ] : tolerance on results [default=0.01]
I tried with 2 T1MRI. It tooks 20 minutes. What kind of images do you use ?
Have you reached a result ?
If you want I could try with your images.
Isa
You could find some information on this part of documentation (Aims command line):
http://brainvisa.info/doc/aimsdata-4.3/ ... 08s02.html
In fact, Brainvisa interfaces the AimsMIRregister command line, which is usable in a terminal too.
If you launch : AimsMIRegister -h, you will get some information about options.
When a command is interfaced by BrainVISA, some options can be hidden to make easier to use.
Here the link between brainvisa and command line names :
"reference_threshold" = [ --threshref | --seuilref <FLOAT> ] : relative thresh applied prior to grav cent estimation
"source_threshold" = [ --threshtest | --seuiltest <FLOAT> ] : relative thresh applied prior to grav cent estimation
"reference_reduction_factor" = [ --refstartpyr <S32> ] level of the multiresolution optimization: start resolution level for ref
"error_Epsilon" = [ --error <FLOAT> ] : tolerance on results [default=0.01]
I tried with 2 T1MRI. It tooks 20 minutes. What kind of images do you use ?
Have you reached a result ?
If you want I could try with your images.
Isa
Re: Rigid registration with MI dialog box
Hi,
OK thanks.
Could you explain more about what "level of the multiresolution optimization: start resolution level for ref" and "error_Epsilon = [ --error <FLOAT> ] : tolerance on results [default=0.01]" means...
I did try to co-register a T2 MRI or T2 MRI template with a CT image, but that did not work very well, so I am using mask instead, and that works fairly well. I am just trying to get it faster. So I am wondering if altering these parameters might make the process faster.
Cheers,
Rv
OK thanks.
Could you explain more about what "level of the multiresolution optimization: start resolution level for ref" and "error_Epsilon = [ --error <FLOAT> ] : tolerance on results [default=0.01]" means...
I did try to co-register a T2 MRI or T2 MRI template with a CT image, but that did not work very well, so I am using mask instead, and that works fairly well. I am just trying to get it faster. So I am wondering if altering these parameters might make the process faster.
Cheers,
Rv
__________________________________
Hervé BOUTIN, PhD
Senior Research Scientist
University of Manchester
Faculty of Biology, Medicine and Health
email: herve.boutin@manchester.ac.uk
__________________________________
Hervé BOUTIN, PhD
Senior Research Scientist
University of Manchester
Faculty of Biology, Medicine and Health
email: herve.boutin@manchester.ac.uk
__________________________________
Re: Rigid registration with MI dialog box
Hi,
If you use the "reduction_reference_factor" (it works on reference image), you will damage the image.
For example, if you choose the value "1", then 1 voxel out of 2 in the 3 directions will be damaged.
It is interesting if images doesn't have the same modality in particular with intensity differences.
It seems the case, you could try with a value "2" or "3" too.
(you could do the same thing on source image, if you work with command lines)
Another possibility: you could try by changing the initial mode "ini_with_gravity_center", by default, the registration is initialized by using the gravity center.
In this case, you could initialize the registration with a translation by using "initial_translation_x' and so on.
It is interesting when images are far from each other.
Isa
If you use the "reduction_reference_factor" (it works on reference image), you will damage the image.
For example, if you choose the value "1", then 1 voxel out of 2 in the 3 directions will be damaged.
It is interesting if images doesn't have the same modality in particular with intensity differences.
It seems the case, you could try with a value "2" or "3" too.
(you could do the same thing on source image, if you work with command lines)
Another possibility: you could try by changing the initial mode "ini_with_gravity_center", by default, the registration is initialized by using the gravity center.
In this case, you could initialize the registration with a translation by using "initial_translation_x' and so on.
It is interesting when images are far from each other.
Isa