AMICO Maps histograms general question- Not an issue #173
Replies: 47 comments
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Dear Prasanna, I think this is an effect of the discretization in the dictionary. When you apply the l1 norm to promote sparsity in the solution, only some atoms are retained from all possible combinations that are considered. I had observed similar spikes also in the original NODDI fitting, especially in the OD parameter, where the values attributed to CSF is always the same. Best, |
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Hello, Attached are the comparison of NODDI and AMICO histograms.
Here are the voxels associated with corresponding spikes for ICVF from AMICO results
We have tried adjusting the regularization parameters and following are the results.
Can you please share your thoughts. Thanks, |
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Dear Prasanna, sorry for my delay, I am at the moment on kind of "paternity leave" and have had not much time to work. Sorry for that; I'm trying to catch up with work as fast as I can! What you highlight seems to me related to the discretization AMICO uses in the dictionary. I think the spikes are generated by this discretization that somehow limits the possible output values for the parameters. These values seem in fact widely spread in the brain, and not concentrated in any specific location. Surely there are differences between the original model and the aMICO approximation (as I previously described), but this is another topic. Do you think this could badly influence your analyses? On a side note, we have recently developed an alternative way to fit models within AMICO that can enforce, for free, spatial regularization of the estimations in each voxel; this might help also with the issue you describe here. We have not tested this method yet, but I will speak with @ejcanalesr (the actual person who developed this new solver) and I will discuss with him about its applicability to mitigate the discretization issue you have described. I will keep you posted! |
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Hello Dr. Daducci, Thank you for looking into this. We are comparing the response from both NODDI and AMICO to determine if current NODDI processing can be replaced with AMICO as this is the faster version of NODDI or if there are areas that we need to be cautious about in analyzing the results in tumor regions in addition to normal brain processing. Will keep you posted once we do quantitative analysis in tumor regions. Appreciate your feedback. Thanks, |
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Dear Prasanna, did you finally got any useful information from the comparison between AMICO and NODDI implementations? |
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Hello Dr. Daducci, Can you please suggest if there are any parameters we could adjust to make these two results match. Thanks, |
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To follow up on this, I have run into the same issue with discretization in the ICVF and ODI (running the python version of AMICO). Has there been any progress on optimal paramteres or the method by @ejcanalesr? same comparison, with mean gaussian smoothing of the AMICO OD ouptut, kernel size from left to right = 0.75, 1, 2mm (data resolution = 2x2x2)
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Hello Dr. Dadduci, Can you please point us to the method proposed by @ejcanalesr, we can plan to include it in further analysis. Thanks, |
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Hello Dr. Prasanna, Erick J. Canales-Rodríguez www.fidmag.org http://www.fidmag.org/ Ley de protección de datos: 2016-06-12 18:45 GMT+02:00 goals2008 [email protected]:
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Dear Prasanna, we have started looking into this issue and we have a question for you. We noticed that in your plots the OD index is about 0.7 whereas in the maps released with the tutorial data OD is about 1. Which version of the code and matlab are you using? Thanks, |
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Hello, Thank you for looking into this issue. We are using following Matlab Please let me know if you need more information. Thanks, On Thu, Jul 14, 2016 at 4:47 AM, Alessandro Daducci <
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Dear Prasanna, We have been working on the issue you reported. Fortunately, we have found As we have tested this preliminar version only in our data (as well as in Please, could you send us the data you have used to create the figures We plan to update the toolbox as soon as possible, after verify the Thank you very much for your valuable contribution! Regards, P.S. Please, find attached here a preliminary result from our evaluation Notice that after recomputing the OD maps with the original NODDI, in CSF |
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Sure, I will be happy to test this out, please do share the updated code. I dont have access to the original data right now, but could send you another dataset soon. Thanks, |
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This looks great - I would be happy to test as well on HCP data and a 3-shell 2mm dataset that we have collected in-house. I have been using the python version of AMICO, but would also be open to testing the matlab version. Chirs |
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Attaching it again here.. may be its an issue when sending from email. |
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Hi goals2008, |
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Yes. Thanks, |
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Hi Erick,
Just checking if the fix you have made earlier is available in python
version or in the official matlab version.
Appreciate your efforts.
Thanks,
Prasanna
…On Sat, Oct 8, 2016 at 9:41 AM, Prasanna ***@***.***> wrote:
I have attached 2 screenshots having ICVF and ODI histogram and
qualitative image
- AMICO_Orig
- AMICO_New
Reattaching them.. can you please confirm if you still see issue accessing
them.
Thanks,
Prasanna
On Sat, Oct 8, 2016 at 9:13 AM, Christopher J. Steele <
***@***.***> wrote:
> I don't think it was attached...?
> Sorry for my slowness on testing as well, probably will be able to do
> some more testing in about 2 weeks.
> Chris
>
> —
> You are receiving this because you were mentioned.
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Dear Prasanna,
The fix is not available in the official release yet.
However, we are working in a new different implementation that includes a Rician noise model, and spatial regularization for noise datasets, which may replace that fix.
We are very close to have the final version but still we need some time to test it in different datasets.
Thank you very much for your interest!
Regards,
Erick
________________________________
From: goals2008 <[email protected]>
Sent: Saturday, March 18, 2017 3:34 AM
To: daducci/AMICO
Cc: Canales Rodriguez Erick Jorge; Assign
Subject: Re: [daducci/AMICO] AMICO Maps histograms general question- Not an issue (#8)
Hi Erick,
Just checking if the fix you have made earlier is available in python
version or in the official matlab version.
Appreciate your efforts.
Thanks,
Prasanna
On Sat, Oct 8, 2016 at 9:41 AM, Prasanna ***@***.***> wrote:
I have attached 2 screenshots having ICVF and ODI histogram and
qualitative image
- AMICO_Orig
- AMICO_New
Reattaching them.. can you please confirm if you still see issue accessing
them.
Thanks,
Prasanna
On Sat, Oct 8, 2016 at 9:13 AM, Christopher J. Steele <
***@***.***> wrote:
> I don't think it was attached...?
> Sorry for my slowness on testing as well, probably will be able to do
> some more testing in about 2 weeks.
> Chris
>
> —
> You are receiving this because you were mentioned.
> Reply to this email directly, view it on GitHub
> <#8 (comment)>, or mute
> the thread
> <https://github.com/notifications/unsubscribe-auth/AKY0HQyqgInks9yCxiiDpRcDoQTUmZO_ks5qx6UmgaJpZM4FwQyD>
> .
>
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Thank you Erick! Its great to know that it will be available soon!
On Tue, Mar 21, 2017 at 5:58 AM, Erick J Canales-Rodríguez <
[email protected]> wrote:
… Dear Prasanna,
The fix is not available in the official release yet.
However, we are working in a new different implementation that includes a
Rician noise model, and spatial regularization for noise datasets, which
may replace that fix.
We are very close to have the final version but still we need some time to
test it in different datasets.
Thank you very much for your interest!
Regards,
Erick
________________________________
From: goals2008 ***@***.***>
Sent: Saturday, March 18, 2017 3:34 AM
To: daducci/AMICO
Cc: Canales Rodriguez Erick Jorge; Assign
Subject: Re: [daducci/AMICO] AMICO Maps histograms general question- Not
an issue (#8)
Hi Erick,
Just checking if the fix you have made earlier is available in python
version or in the official matlab version.
Appreciate your efforts.
Thanks,
Prasanna
On Sat, Oct 8, 2016 at 9:41 AM, Prasanna ***@***.***> wrote:
> I have attached 2 screenshots having ICVF and ODI histogram and
> qualitative image
>
> - AMICO_Orig
> - AMICO_New
>
> Reattaching them.. can you please confirm if you still see issue
accessing
> them.
>
> Thanks,
> Prasanna
>
> On Sat, Oct 8, 2016 at 9:13 AM, Christopher J. Steele <
> ***@***.***> wrote:
>
>> I don't think it was attached...?
>> Sorry for my slowness on testing as well, probably will be able to do
>> some more testing in about 2 weeks.
>> Chris
>>
>> —
>> You are receiving this because you were mentioned.
>> Reply to this email directly, view it on GitHub
>> <#8 (comment)>, or
mute
>> the thread
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AKY0HQyqgInks9yCxiiDpRcDoQTUmZO_ks5qx6UmgaJpZM4FwQyD>
>> .
>>
>
>
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***@***.*** in #8: Hi Erick,\n\n
Just checking if the fix you have made earlier is available in
python\nversion or in the official matlab version.\n\nAppreciate your
efforts.\n\nThanks,\nPrasanna\n\nOn Sat, Oct 8, 2016 at 9:41 AM, Prasanna
***@***.***\u003e wrote:\n\n\u003e I have attached 2
screenshots having ICVF and ODI histogram and\n\u003e qualitative
image\n\u003e\n\u003e - AMICO_Orig\n\u003e - AMICO_New\n\u003e\n\u003e
Reattaching them.. can you please confirm if you still see issue
accessing\n\u003e them.\n\u003e\n\u003e Thanks,\n\u003e
Prasanna\n\u003e\n\u003e On Sat, Oct 8, 2016 at 9:13 AM, Christopher J.
Steele \u003c\n\u003e ***@***.***\u003e
wrote:\n\u003e\n\u003e\u003e I don't think it was
attached...?\n\u003e\u003e Sorry for my slowness on testing as well,
probably will be able to do\n\u003e\u003e some more testing in about 2
weeks.\n\u003e\u003e Chris\n\u003e\u003e\n\u003e\u003e —\n\u003e\u003e
You are receiving this because you were mentioned.\n\u003e\u003e Reply to
this email directly, view it on GitHub\n\u003e\u003e \u003chttps://
github.com/daducci/AMICO/issues/8#issuecomment-252426723\u003e
<https://github.com/daducci/AMICO/issues/8#issuecomment-252426723%5Cu003e>,
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This issue is about to reach its anniversary. thanks and please let us know how we can help. |
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Bump -- any progress on this? |
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Hi, I'm also curious whether there has been any progress on this, especially in the python version. I greatly appreciate the speed and stability of the AMICO implementation of NODDI, but it seems as if it is sometimes too stable and prefers certain values. We would like to make comparisons within a set of scans for a study, but as you can see we have a problem with the ICVF (= NDI in the plot) having a predilection for certain values for many regions in the JHU "Eve" WM atlas:
The plot shows the median ICVF of the voxels inside each atlas region vs. the number of voxels in that scans's region in subject space for 128 scans. I like to make these plots to check the quality of both model fitting and atlas registration, and usually expect to see blobbish clusters for each region. The orientation dispersion and ISOVF from AMICO NODDI are not showing any drastic quantization in their plots. Is there any way I can help? If it is delayed by the Rician noise model, I hope you will consider making a release without it, since I am already debiasing my input images. Thanks, Rob Reid |
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My personal impression is that this issue cannot or will not be fixed. If you are looking for faster modelling of NODDI parameters and know how to setup GPU devices you may explore the Microstructure Diffusion Toolbox If you scroll half way down the FAQ page you'll see an example of NODDI modelling and their publication. An added benefit is the software allows testing many models and easily adding your own so it is an interesting way to explore your data and learn concepts if you are so inclined. |
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Thanks! We are doing our diffusion processing with GPUs anyway because of eddy_cuda, but do have a bit of a road bump because the Microstructure Diffusion Toolbox requires python 3. We are using CentOS 7, and I know there are a few ways to install python 3 even on RHEL-based systems, but I will have to work with our system administrator a bit to figure something out. |
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Dear @captainnova , indeed we have to apologize for the long silence!
The good news is that the problem can be solved, and in fact it was! We have had the code ready for long time now, but have no one to port it and integrate to AMICO. We will do our best to port it asap. As a side note, we are working also on porting AMICO to GPU, for an event more dramatic acceleration! We'll keep you posted of course. |
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I'm glad to hear it! Thanks, Rob |
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Dear @daducci , I am having the same issue with the discretization of ICVF values (I'm working on the HCP dataset). Is this implemented into the Python version of AMICO? Or is there a workaround I could use in the meantime (increasing the number of evenly spaced samples in np.linspace(0.1, 0.99, 12) from 12 to 50 maybe?) as mentioned in issue #97 #97 for a similar issue.
I would greatly appreciate any help! Thank you, Stefanie |
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Dear Stefanie, |
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Hello Dr. Daducci,
This is not an issue but general question in regard to histograms for the AMICO maps that are generated. There are spikes showing up at certain intervals for FICVF and OD histograms as attached. When we threshold the image for these values the data seem to be spread across the brain.
Can you please advice if this is expected.
Thanks,
Prasanna
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