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Dear Sir, I have tried alignment using FLIRT, the quality of images is very poor ( Kindly see the attachment - I have tried aligning sMRI+fMRI for few subjects) Thanks Vasudev On 12 January 2017 at 11:01, Anderson M. Winkler <[log in to unmask]> wrote: > Hi Vasudev, > > The quality of the alignment certainly will influence the parcellation. > You would align the images within subject using FLIRT, then the subjects > with each other using FNIRT (that is non-linear). Consult the FSL > documentation. > > All the best, > > Anderson > > > On 11 January 2017 at 15:10, Dev vasu <vasudevamurthy.devulapally@ > gmail.com> wrote: > >> Dear Sir, >> >> Can i align rfMRI +DTI to each subjects Structural data using flirt, my >> only concern is whether such alignment will influence the parcellation >> that i would like to perform on group level. >> >> Thanks >> Vasudev >> >> On 11 January 2017 at 13:55, Anderson M. Winkler <[log in to unmask]> >> wrote: >> >>> Hi Vasudev, >>> >>> Yes, you can. FLIRT works with images that have different types of >>> contrast. Consider using FA when aligning the DTI, though, as opposed to >>> the raw diffusion-weighted images. >>> >>> All the best, >>> >>> Anderson >>> >>> >>> On 10 January 2017 at 15:10, Dev vasu <vasudevamurthy.devulapally@gm >>> ail.com> wrote: >>> >>>> Dear Sir, >>>> >>>> Can i use FLIRT for aligning DTI+fMRI and sMRI ? , I am not sure if >>>> such multimodal alignment will work properly with FLIRT . >>>> >>>> >>>> Thanks >>>> Vasudev >>>> >>>> On 7 January 2017 at 13:04, Anderson M. Winkler <[log in to unmask] >>>> > wrote: >>>> >>>>> Hi Vasudev, >>>>> >>>>> For the alignment, have you tried FLIRT? >>>>> >>>>> Regarding the overall task, I came across this paper yesterday (via >>>>> Twitter): https://arxiv.org/abs/1701.01315. Perhaps it's something >>>>> along these lines you need? >>>>> >>>>> All the best, >>>>> >>>>> Anderson >>>>> >>>>> >>>>> On 6 January 2017 at 14:00, Dev vasu <vasudevamurthy.devulapally@gm >>>>> ail.com> wrote: >>>>> >>>>>> Dear Sir, >>>>>> >>>>>> Is there any approach that i can use for "multi modal data alignment >>>>>> " , i would like accomplish within the subject alignment of multiple >>>>>> modalities like Structural, functional and DTI scans ?. >>>>>> >>>>>> Thanks >>>>>> Vasudev >>>>>> >>>>>> On 6 January 2017 at 12:59, Anderson M. Winkler < >>>>>> [log in to unmask]> wrote: >>>>>> >>>>>>> Hi Vasudev, >>>>>>> >>>>>>> I'm unaware of a tool that would parcellate in the way as you'd >>>>>>> like, although you should be able to do it yourself, e.g., by building a >>>>>>> similarity matrix using some measure or feature of interest that would >>>>>>> encompass all the modalities you are want, then applying a clustering >>>>>>> algorithm. >>>>>>> >>>>>>> All the best, >>>>>>> >>>>>>> Anderson >>>>>>> >>>>>>> >>>>>>> On 5 January 2017 at 11:58, Dev vasu <vasudevamurthy.devulapally@gm >>>>>>> ail.com> wrote: >>>>>>> >>>>>>>> Dear Sir, >>>>>>>> >>>>>>>> I have read the publication from Matthew Glasser, but the scripts >>>>>>>> from Glasser are valid if we have full brain scans of T1w and T2w images >>>>>>>> but there is a problem with my T2w data acquisition, I did no acquire full >>>>>>>> brain T2w images so i cannot use HCP scripts for my study. >>>>>>>> >>>>>>>> I have even read the work of Craddock and his Software tool >>>>>>>> PyclusterROI, but the software is only applicable for rfMRI not DTI scans, >>>>>>>> i would like to know if there is any other journal or software tool which >>>>>>>> can perform group wise multimodal parcellation of T1w, rfMRI,and DTI scans >>>>>>>> of 2 groups of subjects. >>>>>>>> >>>>>>>> >>>>>>>> Thanks >>>>>>>> Vasudev >>>>>>>> >>>>>>>> On 5 January 2017 at 11:52, Anderson M. Winkler < >>>>>>>> [log in to unmask]> wrote: >>>>>>>> >>>>>>>>> Hi Vasudev, >>>>>>>>> >>>>>>>>> There are many different ways in which the brain can be >>>>>>>>> parcellated, based on anatomy, function, and combinations thereof. The >>>>>>>>> paper by Brett et al. (2002, http://www.nature.com/nrn/jour >>>>>>>>> nal/v3/n3/full/nrn756.html) had a different original purpose but >>>>>>>>> it's useful here too in reviewing what different features can mean. And >>>>>>>>> major multimodal parcellation effort using data from the HCP has just been >>>>>>>>> published (Glasser et al, 2016, http://www.nature.com/nature/j >>>>>>>>> ournal/v536/n7615/full/nature18933.html). >>>>>>>>> >>>>>>>>> Given what you seem interested in clustering, perhaps consider as >>>>>>>>> a starting point the work by Craddock et al (Human Brain Mapping, 2012, >>>>>>>>> https://www.ncbi.nlm.nih.gov/pubmed/21769991). Some additional >>>>>>>>> details and the scripts are available freely here >>>>>>>>> <http://ccraddock.github.io/cluster_roi/atlases.html> and here >>>>>>>>> <https://github.com/ccraddock/cluster_roi>. >>>>>>>>> >>>>>>>>> All the best, >>>>>>>>> >>>>>>>>> Anderson >>>>>>>>> >>>>>>>>> >>>>>>>>> On 4 January 2017 at 19:50, Dev vasu < >>>>>>>>> [log in to unmask]> wrote: >>>>>>>>> >>>>>>>>>> Dear Sir, >>>>>>>>>> >>>>>>>>>> Is there any approach where i can perform Group wise multimodal >>>>>>>>>> parcellation, I want to include T1w,T2w,rfMRI, and DTI or 2 groups of >>>>>>>>>> subjects (25 healthy and 25 diseased controls with BLVP) and perform >>>>>>>>>> multimodal clustering on whole brain. If you have some Journals or some >>>>>>>>>> approaches which can useful in performing the analysis i would be really >>>>>>>>>> grateful for your help. >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> Thanks >>>>>>>>>> Vasudev >>>>>>>>>> >>>>>>>>>> On 4 January 2017 at 15:38, Dev vasu < >>>>>>>>>> [log in to unmask]> wrote: >>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> ---------- Forwarded message ---------- >>>>>>>>>>> From: Dev vasu <[log in to unmask]> >>>>>>>>>>> Date: 4 January 2017 at 13:58 >>>>>>>>>>> Subject: Re: [FSL] Group Average parcellation >>>>>>>>>>> To: FSL - FMRIB's Software Library <[log in to unmask]> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Dear Sir, >>>>>>>>>>> >>>>>>>>>>> I would like to measure the neural activity of visual vestibular >>>>>>>>>>> interaction between healthy controls and patients with bilateral >>>>>>>>>>> vestibulopathy ,for this i have thought of using seed based functional >>>>>>>>>>> connectivity to examine visual vestibular changes in BLVP patients in my >>>>>>>>>>> study, >>>>>>>>>>> >>>>>>>>>>> I would like to perform whole brain clustering on 2 groups of >>>>>>>>>>> subjects that i have ( 25 healthy and 25 BLVP ) and extract 600 - 700 ROIs >>>>>>>>>>> using temporal correlation and i feel this is better way to define a seed >>>>>>>>>>> region to investigate functional connectivity changes , kindly let me know >>>>>>>>>>> if there is any thing wrong in my approach, your suggestions are greatly >>>>>>>>>>> appreciated. >>>>>>>>>>> >>>>>>>>>>> I know that we can easily define a seed region on an Atlast ( >>>>>>>>>>> MNI 152 or Harvard oxford atlas ) but i would like use clustering approach >>>>>>>>>>> for whole brain parcellation. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Thanks >>>>>>>>>>> Vasudev >>>>>>>>>>> >>>>>>>>>>> On 4 January 2017 at 12:32, Anderson M. Winkler < >>>>>>>>>>> [log in to unmask]> wrote: >>>>>>>>>>> >>>>>>>>>>>> Hi Vasudev, >>>>>>>>>>>> >>>>>>>>>>>> What feature would you like to drive the parcellation? The ICA >>>>>>>>>>>> itself is a form of soft (fuzzy) parcellation. I'm unsure what you'd like >>>>>>>>>>>> to do. >>>>>>>>>>>> >>>>>>>>>>>> All the best, >>>>>>>>>>>> >>>>>>>>>>>> Anderson >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> On 2 January 2017 at 12:58, Dev vasu < >>>>>>>>>>>> [log in to unmask]> wrote: >>>>>>>>>>>> >>>>>>>>>>>>> Dear FSL community, >>>>>>>>>>>>> >>>>>>>>>>>>> I have 50 Subjects ( 25 healthy controls and 25 patients with >>>>>>>>>>>>> BLVP ), I have performed Group mean ICA , I would like to perform whole >>>>>>>>>>>>> brain parcellation on Group Mean ICA of Healthy controls and Group mean ICA >>>>>>>>>>>>> of patients with BLVP. >>>>>>>>>>>>> >>>>>>>>>>>>> I would like to know the better approach for Group wise >>>>>>>>>>>>> parcellation ( any previous Publications concerning the same topic would be >>>>>>>>>>>>> greatly appreciated ). >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> Thanks >>>>>>>>>>>>> Vasudev >>>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> >>>>>>>>> >>>>>>>> >>>>>>> >>>>>> >>>>> >>>> >>> >> >