Hi all,
I have sets (different subjects) of MR stacks aquired with 2 different sequences one is an EPI and the other is an anatomical scan. For analysis I prefer to avoid co-registration for most of the cases and do registration only for those cases that would "really" need to be co-registered. I would like to know how should I decide if registration is necessary? Other than just visually inspecting the stacks I would like to know if there is any quantitative method for this matter? I would also like to ask another question: say you have coregisterd two images how will you evaluate "the goodness" of registration? What tools ImageJ provid for this purpose? Best, Nas __________________________________________________ Do You Yahoo!? Tired of spam? Yahoo! Mail has the best spam protection around http://mail.yahoo.com |
Hi Nas,
You can test the goodness of registration by assessing the repeatability of some outcome measure - say, the position and dimensions of the transformed image, or whatever it is that you're interested in - some result that you can only get in the registered space. I found the sync windows plugin useful for dealing with registered images. HTH Mike Nas wrote: > Hi all, > > I have sets (different subjects) of MR stacks aquired > with 2 different sequences one is an EPI and the other > is an anatomical scan. For analysis I prefer to avoid > co-registration for most of the cases and do > registration only for those cases that would "really" > need to be co-registered. I would like to know how > should I decide if registration is necessary? Other > than just visually inspecting the stacks I would like > to know if there is any quantitative method for this > matter? > > I would also like to ask another question: say you > have coregisterd two images how will you evaluate "the > goodness" of registration? > > What tools ImageJ provid for this purpose? > > Best, > Nas > > __________________________________________________ > Do You Yahoo!? > Tired of spam? Yahoo! Mail has the best spam protection around > http://mail.yahoo.com > -- Michael Doube BPhil BVSc MRCVS PhD Student Dental Institute Queen Mary, University of London New Rd London E1 1BB United Kingdom Phone +44 (0)20 7377 7000 ext 2681 |
In reply to this post by Nas-5
I just remembered the other thing: if you do repeat registrations and
save the results, then subtract one transformed image from the other transform repeats, you will get black images if registration is perfectly repeatable, or embossed-looking images if they're not. The amount of 'embossing' is an expression of how repeatable your registration is. You could do some maths on the embossed / error images to quantify the amount of difference I guess. Mike Nas wrote: > Hi all, > > I have sets (different subjects) of MR stacks aquired > with 2 different sequences one is an EPI and the other > is an anatomical scan. For analysis I prefer to avoid > co-registration for most of the cases and do > registration only for those cases that would "really" > need to be co-registered. I would like to know how > should I decide if registration is necessary? Other > than just visually inspecting the stacks I would like > to know if there is any quantitative method for this > matter? > > I would also like to ask another question: say you > have coregisterd two images how will you evaluate "the > goodness" of registration? > > What tools ImageJ provid for this purpose? > > Best, > Nas > > __________________________________________________ > Do You Yahoo!? > Tired of spam? Yahoo! Mail has the best spam protection around > http://mail.yahoo.com > |
In reply to this post by Michael Doube-2
On Thursday 03 August 2006 16:25, Michael Doube wrote:
> You can test the goodness of registration by assessing the repeatability > of some outcome measure - say, the position and dimensions of the > transformed image, or whatever it is that you're interested in - some > result that you can only get in the registered space. I am not sure that repeatability is directrelated to gly oodness of fit. Suppose that the registration is consistently bad. By your argument the goodness of fit is good despite that the registration is bad. I think that in the case of registration one has to come up with some measure of distance between the images being registered. Finding out how the registration algorithm works may give you a clue (since the algorithm has to search for an optimal solution). Cheers, Gabriel |
In reply to this post by Nas-5
Nas,
Do the image stacks have images with the same dimensions? If so, you might try overlaying the two stacks as color images with the first stack in, say, Red, and the 2nd stack in, say, Blue. Mis-registrations will be obvious. I think you will need a 3rd stack of zero value images for the green channel. You can convert the 3 stacks to an RGB stack with "Image/Color/RGB Merge". Or you can use your original stacks with the ColorComparison plugin. Either way, the stacks must first be converted to 8 bit grayscale. best, William O'Connell -------------- Original message ---------------------- From: Nas <[hidden email]> > Hi all, > > I have sets (different subjects) of MR stacks aquired > with 2 different sequences one is an EPI and the other > is an anatomical scan. For analysis I prefer to avoid > co-registration for most of the cases and do > registration only for those cases that would "really" > need to be co-registered. I would like to know how > should I decide if registration is necessary? Other > than just visually inspecting the stacks I would like > to know if there is any quantitative method for this > matter? > > I would also like to ask another question: say you > have coregisterd two images how will you evaluate "the > goodness" of registration? > > What tools ImageJ provid for this purpose? > > Best, > Nas > > __________________________________________________ > Do You Yahoo!? > Tired of spam? Yahoo! Mail has the best spam protection around > http://mail.yahoo.com |
In reply to this post by Gabriel Landini
Hi Gabriel,
Thank you for your reply. Actually I'm trying to chose between few algorithms that I have based on their outcome. Therefore , as these algorithms either use different similarity functions (and as a result different optimization cost functions and criteria) or even if they chose the same similarity functions they vary in other modules in implementation. So I would need to compare them based on only the outcome and decide which algorithm and setting gives me the best results. As you have also mentioned I might need to come up with some measure of distance between the original image and the registered images from various algorithms... something like abolute difference maybe.. Best, Nasim Gabriel Landini <[hidden email]> wrote: On Thursday 03 August 2006 16:25, Michael Doube wrote: > You can test the goodness of registration by assessing the repeatability > of some outcome measure - say, the position and dimensions of the > transformed image, or whatever it is that you're interested in - some > result that you can only get in the registered space. I am not sure that repeatability is directrelated to gly oodness of fit. Suppose that the registration is consistently bad. By your argument the goodness of fit is good despite that the registration is bad. I think that in the case of registration one has to come up with some measure of distance between the images being registered. Finding out how the registration algorithm works may give you a clue (since the algorithm has to search for an optimal solution). Cheers, Gabriel --------------------------------- How low will we go? Check out Yahoo! Messengers low PC-to-Phone call rates. |
In reply to this post by William O'Connell
Hi William,
Thank you very much for your replies. Yes, images have same dimensions. I was not familiar with this feature of ImageJ. It really makes assessment of registrations very easy! It is very helpful.Thank you for this. Best, Nasim William O'Connell <[hidden email]> wrote: Nas, Do the image stacks have images with the same dimensions? If so, you might try overlaying the two stacks as color images with the first stack in, say, Red, and the 2nd stack in, say, Blue. Mis-registrations will be obvious. I think you will need a 3rd stack of zero value images for the green channel. You can convert the 3 stacks to an RGB stack with "Image/Color/RGB Merge". Or you can use your original stacks with the ColorComparison plugin. Either way, the stacks must first be converted to 8 bit grayscale. best, William O'Connell -------------- Original message ---------------------- From: Nas > Hi all, > > I have sets (different subjects) of MR stacks aquired > with 2 different sequences one is an EPI and the other > is an anatomical scan. For analysis I prefer to avoid > co-registration for most of the cases and do > registration only for those cases that would "really" > need to be co-registered. I would like to know how > should I decide if registration is necessary? Other > than just visually inspecting the stacks I would like > to know if there is any quantitative method for this > matter? > > I would also like to ask another question: say you > have coregisterd two images how will you evaluate "the > goodness" of registration? > > What tools ImageJ provid for this purpose? > > Best, > Nas > > __________________________________________________ > Do You Yahoo!? > Tired of spam? Yahoo! Mail has the best spam protection around > http://mail.yahoo.com --------------------------------- Do you Yahoo!? Next-gen email? Have it all with the all-new Yahoo! Mail Beta. |
Nas,
I just posted a new version of the plugin Convolve 3D on my web site. It computes correlations and, especially, correlation coefficients between stacks. It might do just what you need. It only addresses translations, though. Rotations and scale changes are outside its scope. Bob Robert P. Dougherty, Ph.D. President, OptiNav, Inc. Phone (425) 467-1118 Fax (425) 467-1119 www.optinav.com > -------------- Original message ---------------------- > From: Nas > > Hi all, > > > > I have sets (different subjects) of MR stacks aquired > > with 2 different sequences one is an EPI and the other > > is an anatomical scan. For analysis I prefer to avoid > > co-registration for most of the cases and do > > registration only for those cases that would "really" > > need to be co-registered. I would like to know how > > should I decide if registration is necessary? Other > > than just visually inspecting the stacks I would like > > to know if there is any quantitative method for this > > matter? > > > > I would also like to ask another question: say you > > have coregisterd two images how will you evaluate "the > > goodness" of registration? > > > > What tools ImageJ provid for this purpose? > > > > Best, > > Nas |
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