Dear all,
I understand that the various "path.pd" image files that are created by TRACULA represent a posterior distribution over the corresponding tract location, but I was wondering if someone could explain to me exactly what the values in these images mean. I assume that they are not probabilities as such, since they have values ranging up to several hundreds.
Thanks in advance, Jon
Hi Jon - The path.pd volumes are indeed the posterior probability distributions of each pathway. They are not normalized to a sum of 1 though b/c they're estimated by a sampling algorithm (drawing sample paths from this unknown distribution and adding up the sample paths, instead of estimating the distribution directly).
Hope this helps, a.y
On Fri, 9 Nov 2012, Jon Clayden wrote:
Dear all, I understand that the various "path.pd" image files that are created by TRACULA represent a posterior distribution over the corresponding tract location, but I was wondering if someone could explain to me exactly what the values in these images mean. I assume that they are not probabilities as such, since they have values ranging up to several hundreds.
Thanks in advance, Jon
That does help - many thanks!
Jon
On 9 November 2012 15:56, Anastasia Yendiki ayendiki@nmr.mgh.harvard.eduwrote:
Hi Jon - The path.pd volumes are indeed the posterior probability distributions of each pathway. They are not normalized to a sum of 1 though b/c they're estimated by a sampling algorithm (drawing sample paths from this unknown distribution and adding up the sample paths, instead of estimating the distribution directly).
Hope this helps, a.y
On Fri, 9 Nov 2012, Jon Clayden wrote:
Dear all,
I understand that the various "path.pd" image files that are created by TRACULA represent a posterior distribution over the corresponding tract location, but I was wondering if someone could explain to me exactly what the values in these images mean. I assume that they are not probabilities as such, since they have values ranging up to several hundreds.
Thanks in advance, Jon
The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/**compliancelinehttp://www.partners.org/complianceline. If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Hi Anastasia, Just follow up on this thread.. If 5000 samples were used for each voxel, how can I normalize the intensity of path.pd volumes to a sum of 1 ? Also what thresholding value was chosen to calculate the tract volume, shown in the pathstats.overall.txt ?
Thanks. ping
On Fri, Nov 9, 2012 at 10:56 AM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Jon - The path.pd volumes are indeed the posterior probability distributions of each pathway. They are not normalized to a sum of 1 though b/c they're estimated by a sampling algorithm (drawing sample paths from this unknown distribution and adding up the sample paths, instead of estimating the distribution directly).
Hope this helps, a.y
On Fri, 9 Nov 2012, Jon Clayden wrote:
Dear all, I understand that the various "path.pd" image files that are created by TRACULA represent a posterior distribution over the corresponding tract location, but I was wondering if someone could explain to me exactly what the values in these images mean. I assume that they are not probabilities as such, since they have values ranging up to several hundreds.
Thanks in advance, Jon
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Hi Ping - The total number of paths that were sampled doesn't enter the picture. Of these sampled paths, some get rejected and some get accepted. The latter are added up to get an estimate of the posterior probability distribution of the path (that's path.pd.nii.gz). You can normalize to a total sum of 1 by diving that volume with its total sum.
The default threshold is 20% of the maximum value, to get rid of the tails of the distribution (which would need more total samples to converge than the center of the distribution anyway). You can of course find your own averages at a different threshold from path.pd.nii.gz if you wish.
Hope this helps, a.y
On Fri, 14 Dec 2012, Ping-Hong Yeh wrote:
Hi Anastasia, Just follow up on this thread.. If 5000 samples were used for each voxel, how can I normalize the intensity of path.pd volumes to a sum of 1 ? Also what thresholding value was chosen to calculate the tract volume, shown in the pathstats.overall.txt ?
Thanks. ping
On Fri, Nov 9, 2012 at 10:56 AM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Jon - The path.pd volumes are indeed the posterior probability distributions of each pathway. They are not normalized to a sum of 1 though b/c they're estimated by a sampling algorithm (drawing sample paths from this unknown distribution and adding up the sample paths, instead of estimating the distribution directly).
Hope this helps, a.y
On Fri, 9 Nov 2012, Jon Clayden wrote:
Dear all, I understand that the various "path.pd" image files that are created by TRACULA represent a posterior distribution over the corresponding tract location, but I was wondering if someone could explain to me exactly what the values in these images mean. I assume that they are not probabilities as such, since they have values ranging up to several hundreds.
Thanks in advance, Jon
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The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Hi Anastasia,
Thank you the answers. One more question, if I'd like to use the scalar images created by other methods, e.g. non-linear fitting, how can I feed this images to output the stats like the pathstats? I knew the "tractstats2table" will do the jobs, but it is binarized and hard-coded.
ping On Thu, Dec 20, 2012 at 5:30 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Ping - The total number of paths that were sampled doesn't enter the picture. Of these sampled paths, some get rejected and some get accepted. The latter are added up to get an estimate of the posterior probability distribution of the path (that's path.pd.nii.gz). You can normalize to a total sum of 1 by diving that volume with its total sum.
The default threshold is 20% of the maximum value, to get rid of the tails of the distribution (which would need more total samples to converge than the center of the distribution anyway). You can of course find your own averages at a different threshold from path.pd.nii.gz if you wish.
Hope this helps, a.y
On Fri, 14 Dec 2012, Ping-Hong Yeh wrote:
Hi Anastasia, Just follow up on this thread.. If 5000 samples were used for each voxel, how can I normalize the intensity of path.pd volumes to a sum of 1 ? Also what thresholding value was chosen to calculate the tract volume, shown in the pathstats.overall.txt ?
Thanks. ping
On Fri, Nov 9, 2012 at 10:56 AM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Jon - The path.pd volumes are indeed the posterior probability distributions of each pathway. They are not normalized to a sum of 1 though b/c they're estimated by a sampling algorithm (drawing sample paths from this unknown distribution and adding up the sample paths, instead of estimating the distribution directly).
Hope this helps, a.y
On Fri, 9 Nov 2012, Jon Clayden wrote:
Dear all, I understand that the various "path.pd" image files that are created by TRACULA represent a posterior distribution over the corresponding tract location, but I was wondering if someone could explain to me exactly what the values in these images mean. I assume that they are not probabilities as such, since they have values ranging up to several hundreds.
Thanks in advance, Jon
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Hi Ping - Are you asking how you can produced the stats? You could use fslstats with path.pd.nii.gz as the mask, and redirect the outputs to a file that looks like pathstats.overall.txt. You could either keep the same names for the measures or edit the tractstats2table script to change the names that it allows. Hope I answered your questions.
a.y
On Fri, 21 Dec 2012, Ping-Hong Yeh wrote:
Hi Anastasia,
Thank you the answers. One more question, if I'd like to use the scalar images created by other methods, e.g. non-linear fitting, how can I feed this images to output the stats like the pathstats? I knew the "tractstats2table" will do the jobs, but it is binarized and hard-coded.
ping On Thu, Dec 20, 2012 at 5:30 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Ping - The total number of paths that were sampled doesn't enter the picture. Of these sampled paths, some get rejected and some get accepted. The latter are added up to get an estimate of the posterior probability distribution of the path (that's path.pd.nii.gz). You can normalize to a total sum of 1 by diving that volume with its total sum.
The default threshold is 20% of the maximum value, to get rid of the tails of the distribution (which would need more total samples to converge than the center of the distribution anyway). You can of course find your own averages at a different threshold from path.pd.nii.gz if you wish.
Hope this helps, a.y
On Fri, 14 Dec 2012, Ping-Hong Yeh wrote:
Hi Anastasia, Just follow up on this thread.. If 5000 samples were used for each voxel, how can I normalize the intensity of path.pd volumes to a sum of 1 ? Also what thresholding value was chosen to calculate the tract volume, shown in the pathstats.overall.txt ?
Thanks. ping
On Fri, Nov 9, 2012 at 10:56 AM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Jon - The path.pd volumes are indeed the posterior probability distributions of each pathway. They are not normalized to a sum of 1 though b/c they're estimated by a sampling algorithm (drawing sample paths from this unknown distribution and adding up the sample paths, instead of estimating the distribution directly).
Hope this helps, a.y
On Fri, 9 Nov 2012, Jon Clayden wrote:
Dear all, I understand that the various "path.pd" image files that are created by TRACULA represent a posterior distribution over the corresponding tract location, but I was wondering if someone could explain to me exactly what the values in these images mean. I assume that they are not probabilities as such, since they have values ranging up to several hundreds.
Thanks in advance, Jon
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Sorry for not being clear. I meant how to calculate path length based on path.pd.nii.gz, and the Center and Weight Average of the scalar images? Thanks.
On Fri, Dec 21, 2012 at 3:45 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Ping - Are you asking how you can produced the stats? You could use fslstats with path.pd.nii.gz as the mask, and redirect the outputs to a file that looks like pathstats.overall.txt. You could either keep the same names for the measures or edit the tractstats2table script to change the names that it allows. Hope I answered your questions.
a.y
On Fri, 21 Dec 2012, Ping-Hong Yeh wrote:
Hi Anastasia,
Thank you the answers. One more question, if I'd like to use the scalar images created by other methods, e.g. non-linear fitting, how can I feed this images to output the stats like the pathstats? I knew the "tractstats2table" will do the jobs, but it is binarized and hard-coded.
ping On Thu, Dec 20, 2012 at 5:30 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Ping - The total number of paths that were sampled doesn't enter the picture. Of these sampled paths, some get rejected and some get accepted. The latter are added up to get an estimate of the posterior probability distribution of the path (that's path.pd.nii.gz). You can normalize to a total sum of 1 by diving that volume with its total sum.
The default threshold is 20% of the maximum value, to get rid of the tails of the distribution (which would need more total samples to converge than the center of the distribution anyway). You can of course find your own averages at a different threshold from path.pd.nii.gz if you wish.
Hope this helps, a.y
On Fri, 14 Dec 2012, Ping-Hong Yeh wrote:
Hi Anastasia, Just follow up on this thread.. If 5000 samples were used for each voxel, how can I normalize the intensity of path.pd volumes to a sum of 1 ? Also what thresholding value was chosen to calculate the tract volume, shown in the pathstats.overall.txt ?
Thanks. ping
On Fri, Nov 9, 2012 at 10:56 AM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Jon - The path.pd volumes are indeed the posterior probability distributions of each pathway. They are not normalized to a sum of 1 though b/c they're estimated by a sampling algorithm (drawing sample paths from this unknown distribution and adding up the sample paths, instead of estimating the distribution directly).
Hope this helps, a.y
On Fri, 9 Nov 2012, Jon Clayden wrote:
Dear all, I understand that the various "path.pd" image files that are created by TRACULA represent a posterior distribution over the corresponding tract location, but I was wondering if someone could explain to me exactly what the values in these images mean. I assume that they are not probabilities as such, since they have values ranging up to several hundreds.
Thanks in advance, Jon
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Path length: that's independent of any external scalar images. Weighted average: you multiply with the actual value in path.pd.nii.gz, then average. Center average: you average only over the voxels in path.map.nii.gz.
On Fri, 21 Dec 2012, Ping-Hong Yeh wrote:
Sorry for not being clear. I meant how to calculate path length based on path.pd.nii.gz, and the Center and Weight Average of the scalar images? Thanks.
On Fri, Dec 21, 2012 at 3:45 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Ping - Are you asking how you can produced the stats? You could use fslstats with path.pd.nii.gz as the mask, and redirect the outputs to a file that looks like pathstats.overall.txt. You could either keep the same names for the measures or edit the tractstats2table script to change the names that it allows. Hope I answered your questions.
a.y
On Fri, 21 Dec 2012, Ping-Hong Yeh wrote:
Hi Anastasia,
Thank you the answers. One more question, if I'd like to use the scalar images created by other methods, e.g. non-linear fitting, how can I feed this images to output the stats like the pathstats? I knew the "tractstats2table" will do the jobs, but it is binarized and hard-coded.
ping On Thu, Dec 20, 2012 at 5:30 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Ping - The total number of paths that were sampled doesn't enter the picture. Of these sampled paths, some get rejected and some get accepted. The latter are added up to get an estimate of the posterior probability distribution of the path (that's path.pd.nii.gz). You can normalize to a total sum of 1 by diving that volume with its total sum.
The default threshold is 20% of the maximum value, to get rid of the tails of the distribution (which would need more total samples to converge than the center of the distribution anyway). You can of course find your own averages at a different threshold from path.pd.nii.gz if you wish.
Hope this helps, a.y
On Fri, 14 Dec 2012, Ping-Hong Yeh wrote:
Hi Anastasia, Just follow up on this thread.. If 5000 samples were used for each voxel, how can I normalize the intensity of path.pd volumes to a sum of 1 ? Also what thresholding value was chosen to calculate the tract volume, shown in the pathstats.overall.txt ?
Thanks. ping
On Fri, Nov 9, 2012 at 10:56 AM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Jon - The path.pd volumes are indeed the posterior probability distributions of each pathway. They are not normalized to a sum of 1 though b/c they're estimated by a sampling algorithm (drawing sample paths from this unknown distribution and adding up the sample paths, instead of estimating the distribution directly).
Hope this helps, a.y
On Fri, 9 Nov 2012, Jon Clayden wrote:
> Dear all, > I understand that the various "path.pd" image files that are created > by > TRACULA represent a posterior > distribution over the corresponding tract location, but I was > wondering > if someone could explain to me > exactly what the values in these images mean. I assume that they are > not > probabilities as such, since they > have values ranging up to several hundreds. > > Thanks in advance, > Jon > > _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
So how was the path length estimated? Thanks again.
On Fri, Dec 21, 2012 at 4:07 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Path length: that's independent of any external scalar images. Weighted average: you multiply with the actual value in path.pd.nii.gz, then average. Center average: you average only over the voxels in path.map.nii.gz.
On Fri, 21 Dec 2012, Ping-Hong Yeh wrote:
Sorry for not being clear. I meant how to calculate path length based on path.pd.nii.gz, and the Center and Weight Average of the scalar images? Thanks.
On Fri, Dec 21, 2012 at 3:45 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Ping - Are you asking how you can produced the stats? You could use fslstats with path.pd.nii.gz as the mask, and redirect the outputs to a file that looks like pathstats.overall.txt. You could either keep the same names for the measures or edit the tractstats2table script to change the names that it allows. Hope I answered your questions.
a.y
On Fri, 21 Dec 2012, Ping-Hong Yeh wrote:
Hi Anastasia,
Thank you the answers. One more question, if I'd like to use the scalar images created by other methods, e.g. non-linear fitting, how can I feed this images to output the stats like the pathstats? I knew the "tractstats2table" will do the jobs, but it is binarized and hard-coded.
ping On Thu, Dec 20, 2012 at 5:30 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Ping - The total number of paths that were sampled doesn't enter the picture. Of these sampled paths, some get rejected and some get accepted. The latter are added up to get an estimate of the posterior probability distribution of the path (that's path.pd.nii.gz). You can normalize to a total sum of 1 by diving that volume with its total sum.
The default threshold is 20% of the maximum value, to get rid of the tails of the distribution (which would need more total samples to converge than the center of the distribution anyway). You can of course find your own averages at a different threshold from path.pd.nii.gz if you wish.
Hope this helps, a.y
On Fri, 14 Dec 2012, Ping-Hong Yeh wrote:
Hi Anastasia, Just follow up on this thread.. If 5000 samples were used for each voxel, how can I normalize the intensity of path.pd volumes to a sum of 1 ? Also what thresholding value was chosen to calculate the tract volume, shown in the pathstats.overall.txt ?
Thanks. ping
On Fri, Nov 9, 2012 at 10:56 AM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote: > > > > > Hi Jon - The path.pd volumes are indeed the posterior probability > distributions of each pathway. They are not normalized to a sum of 1 > though b/c they're estimated by a sampling algorithm (drawing sample > paths > from this unknown distribution and adding up the sample paths, > instead > of > estimating the distribution directly). > > Hope this helps, > a.y > > On Fri, 9 Nov 2012, Jon Clayden wrote: > >> Dear all, >> I understand that the various "path.pd" image files that are created >> by >> TRACULA represent a posterior >> distribution over the corresponding tract location, but I was >> wondering >> if someone could explain to me >> exactly what the values in these images mean. I assume that they are >> not >> probabilities as such, since they >> have values ranging up to several hundreds. >> >> Thanks in advance, >> Jon >> >> > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > The information in this e-mail is intended only for the person to > whom > it > is > addressed. If you believe this e-mail was sent to you in error and > the > e-mail > contains patient information, please contact the Partners Compliance > HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to > you > in > error > but does not contain patient information, please contact the sender > and > properly > dispose of the e-mail. > _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Sample paths are drawn to estimate path.pd.nii.gz via MCMC. It's the average of the length of all path samples that are accepted for inclusion in path.pd.nii.gz.
On Fri, 21 Dec 2012, Ping-Hong Yeh wrote:
So how was the path length estimated? Thanks again.
On Fri, Dec 21, 2012 at 4:07 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Path length: that's independent of any external scalar images. Weighted average: you multiply with the actual value in path.pd.nii.gz, then average. Center average: you average only over the voxels in path.map.nii.gz.
On Fri, 21 Dec 2012, Ping-Hong Yeh wrote:
Sorry for not being clear. I meant how to calculate path length based on path.pd.nii.gz, and the Center and Weight Average of the scalar images? Thanks.
On Fri, Dec 21, 2012 at 3:45 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Ping - Are you asking how you can produced the stats? You could use fslstats with path.pd.nii.gz as the mask, and redirect the outputs to a file that looks like pathstats.overall.txt. You could either keep the same names for the measures or edit the tractstats2table script to change the names that it allows. Hope I answered your questions.
a.y
On Fri, 21 Dec 2012, Ping-Hong Yeh wrote:
Hi Anastasia,
Thank you the answers. One more question, if I'd like to use the scalar images created by other methods, e.g. non-linear fitting, how can I feed this images to output the stats like the pathstats? I knew the "tractstats2table" will do the jobs, but it is binarized and hard-coded.
ping On Thu, Dec 20, 2012 at 5:30 PM, Anastasia Yendiki ayendiki@nmr.mgh.harvard.edu wrote:
Hi Ping - The total number of paths that were sampled doesn't enter the picture. Of these sampled paths, some get rejected and some get accepted. The latter are added up to get an estimate of the posterior probability distribution of the path (that's path.pd.nii.gz). You can normalize to a total sum of 1 by diving that volume with its total sum.
The default threshold is 20% of the maximum value, to get rid of the tails of the distribution (which would need more total samples to converge than the center of the distribution anyway). You can of course find your own averages at a different threshold from path.pd.nii.gz if you wish.
Hope this helps, a.y
On Fri, 14 Dec 2012, Ping-Hong Yeh wrote:
> Hi Anastasia, > Just follow up on this thread.. > If 5000 samples were used for each voxel, how can I normalize the > intensity of path.pd volumes to a sum of 1 ? > Also what thresholding value was chosen to calculate the tract volume, > shown in the pathstats.overall.txt ? > > Thanks. > ping > > > > On Fri, Nov 9, 2012 at 10:56 AM, Anastasia Yendiki > ayendiki@nmr.mgh.harvard.edu wrote: >> >> >> >> >> Hi Jon - The path.pd volumes are indeed the posterior probability >> distributions of each pathway. They are not normalized to a sum of 1 >> though b/c they're estimated by a sampling algorithm (drawing sample >> paths >> from this unknown distribution and adding up the sample paths, >> instead >> of >> estimating the distribution directly). >> >> Hope this helps, >> a.y >> >> On Fri, 9 Nov 2012, Jon Clayden wrote: >> >>> Dear all, >>> I understand that the various "path.pd" image files that are created >>> by >>> TRACULA represent a posterior >>> distribution over the corresponding tract location, but I was >>> wondering >>> if someone could explain to me >>> exactly what the values in these images mean. I assume that they are >>> not >>> probabilities as such, since they >>> have values ranging up to several hundreds. >>> >>> Thanks in advance, >>> Jon >>> >>> >> _______________________________________________ >> Freesurfer mailing list >> Freesurfer@nmr.mgh.harvard.edu >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >> >> >> The information in this e-mail is intended only for the person to >> whom >> it >> is >> addressed. If you believe this e-mail was sent to you in error and >> the >> e-mail >> contains patient information, please contact the Partners Compliance >> HelpLine at >> http://www.partners.org/complianceline . If the e-mail was sent to >> you >> in >> error >> but does not contain patient information, please contact the sender >> and >> properly >> dispose of the e-mail. >> > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > >
freesurfer@nmr.mgh.harvard.edu
-
Anastasia Yendiki -
Jon Clayden -
Ping-Hong Yeh