Working with very large datasets

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Working with very large datasets

arumiat
This post has NOT been accepted by the mailing list yet.
Hi Slicer community,

I've been lucky enough to be passed some very beautiful datasets using the BriteVu contrast agent
http://www.scarletimaging.com/

I'm keen to start working with them but they are extremely large (~5GB), and my system chokes on them, Slicer essentially freezes and I can't do much, and end up having to force quit. This has never happened before, and I'm on a pretty decent spec laptop so I'm a bit surprised..
i7
16GB system RAM
Nvidia 870M w 6GB video RAM
SSD
64GB Windows
Slicer 4.4

Is this a system memory issue? Would upgrading to 32GB RAM help get around this do you think? Any other tips on things I could try?

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Working with very large datasets

arumiat
Hi Slicer community,

I've been lucky enough to be passed some very beautiful datasets using the
BriteVu contrast agent
http://www.scarletimaging.com/ <http://www.scarletimaging.com/>  

I'm keen to start working with them but they are extremely large (~5GB), and
my system chokes on them, Slicer essentially freezes and I can't do much,
and end up having to force quit. This has never happened before, and I'm on
a pretty decent spec laptop so I'm a bit surprised..
i7
16GB system RAM
Nvidia 870M w 6GB video RAM
SSD
64GB Windows
Slicer 4.4

Is this a system memory issue? Would upgrading to 32GB RAM help get around
this do you think? Any other tips on things I could try?





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Re: Working with very large datasets

arumiat
*From Murat: */Depending on what you are trying to do, you might be running
out of memory. Is the dataset 5GB compressed? If so, you are definitely
running out of memory.

Again depending on what you want to do 32GB RAM may not resolve your issues.
You may need much more memory. Or you can try to resample (reduce) the
volume to make it work within the confines of your memory./

Hi Murat,

Thank you. I'm not sure if it's compressed, is there a way to tell? I just
took a look and each individual .dcm file is 2,050KB so I'm thinking it
isn't! How would you recommend compressing them all if this is the case?
The aim is to extract 3D models from it of vasculature, so lossless
compression would be best.

Are you also able to suggest how to to resample the volume to achieve better
performance? The ResampleScalarVolume module?

Thanks in advance,
T



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Re: Working with very large datasets

arumiat
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In reply to this post by arumiat
From Murat: Depending on what you are trying to do, you might be running out of memory. Is the dataset 5GB compressed? If so, you are definitely running out of memory.

Again depending on what you want to do 32GB RAM may not resolve your issues. You may need much more memory. Or you can try to resample (reduce) the volume to make it work within the confines of your memory.


Hi Murat,

Thank you. I'm not sure if it's compressed, is there a way to tell? I just took a look and each individual .dcm file is 2,050KB so I'm thinking it isn't! How would you recommend compressing them all if this is the case?  The aim is to extract 3D models from it of vasculature, so lossless compression would be best.

Are you also able to suggest how to to resample the volume to achieve better performance? The ResampleScalarVolume module?

Thanks in advance,
T
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Re: Working with very large datasets

Fabien PERTUY
In reply to this post by arumiat
Hi,

I had problems using Slicer with 4-8GB datasets as well, but in my case not only the system freezes but it sometime just won't open the file.
As I use a system with similar specs as yours, but more RAM, I would say it is not a RAM issue (at least RAM won't be the only one).

Does anybody knows whether Slicer is able or not to manage >4GB data, or if some optimizations could be required ?

Fabien

-----Message d'origine-----
De : [hidden email] [mailto:[hidden email]] De la part de arumiat
Envoyé : lundi 25 janvier 2016 23:38
À : SPL Slicer Users <[hidden email]>
Objet : [slicer-users] Working with very large datasets

Hi Slicer community,

I've been lucky enough to be passed some very beautiful datasets using the BriteVu contrast agent http://www.scarletimaging.com/ <http://www.scarletimaging.com/>  

I'm keen to start working with them but they are extremely large (~5GB), and my system chokes on them, Slicer essentially freezes and I can't do much, and end up having to force quit. This has never happened before, and I'm on a pretty decent spec laptop so I'm a bit surprised..
i7
16GB system RAM
Nvidia 870M w 6GB video RAM
SSD
64GB Windows
Slicer 4.4

Is this a system memory issue? Would upgrading to 32GB RAM help get around this do you think? Any other tips on things I could try?





--
View this message in context: http://slicer-users.65878.n3.nabble.com/Working-with-very-large-datasets-tp4029896.html
Sent from the slicer-users mailing list archive at Nabble.com.
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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.
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Re: Working with very large datasets

Steve Pieper-2
Hi Guys - 

A lot will depend on the system and what operations you intend to do.  As an example on my mac with 64 gig of ram I can open and view a microCT dataset that is over 10G uncompressed, but most operations are impractical.

There is research on large volume processing being done using the same core infrastructure as Slicer (e.g. running VTK on clusters) but we haven't brought that into the Slicer environment.

For now it's best to downsample or crop to match the hardware you have access to.

Best,
Steve

On Tue, Jan 26, 2016 at 5:26 AM, Fabien PERTUY <[hidden email]> wrote:
Hi,

I had problems using Slicer with 4-8GB datasets as well, but in my case not only the system freezes but it sometime just won't open the file.
As I use a system with similar specs as yours, but more RAM, I would say it is not a RAM issue (at least RAM won't be the only one).

Does anybody knows whether Slicer is able or not to manage >4GB data, or if some optimizations could be required ?

Fabien

-----Message d'origine-----
De : [hidden email] [mailto:[hidden email]] De la part de arumiat
Envoyé : lundi 25 janvier 2016 23:38
À : SPL Slicer Users <[hidden email]>
Objet : [slicer-users] Working with very large datasets

Hi Slicer community,

I've been lucky enough to be passed some very beautiful datasets using the BriteVu contrast agent http://www.scarletimaging.com/ <http://www.scarletimaging.com/>

I'm keen to start working with them but they are extremely large (~5GB), and my system chokes on them, Slicer essentially freezes and I can't do much, and end up having to force quit. This has never happened before, and I'm on a pretty decent spec laptop so I'm a bit surprised..
i7
16GB system RAM
Nvidia 870M w 6GB video RAM
SSD
64GB Windows
Slicer 4.4

Is this a system memory issue? Would upgrading to 32GB RAM help get around this do you think? Any other tips on things I could try?





--
View this message in context: http://slicer-users.65878.n3.nabble.com/Working-with-very-large-datasets-tp4029896.html
Sent from the slicer-users mailing list archive at Nabble.com.
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contains patient information, please contact the Partners Compliance HelpLine at
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Re: Working with very large datasets

arumiat
In reply to this post by Fabien PERTUY
Thanks Steve,

I imagine these files are currently TIFF? Is there a way to batch process them to JPEG-2000 using external software or something?

Is downsampling done via the ResampleScalarVolume?

Thanks,
T

------------------------------------
V A L A design
+ 4 4 (0) 2 0 3 6 3 7 0 0 6 2
IVALA LTD.   REG NO.7931234


On 26 January 2016 at 14:38, Steve Pieper <[hidden email]> wrote:
Hi Guys - 

A lot will depend on the system and what operations you intend to do.  As an example on my mac with 64 gig of ram I can open and view a microCT dataset that is over 10G uncompressed, but most operations are impractical.

There is research on large volume processing being done using the same core infrastructure as Slicer (e.g. running VTK on clusters) but we haven't brought that into the Slicer environment.

For now it's best to downsample or crop to match the hardware you have access to.

Best,
Steve

On Tue, Jan 26, 2016 at 5:26 AM, Fabien PERTUY <[hidden email]> wrote:
Hi,

I had problems using Slicer with 4-8GB datasets as well, but in my case not only the system freezes but it sometime just won't open the file.
As I use a system with similar specs as yours, but more RAM, I would say it is not a RAM issue (at least RAM won't be the only one).

Does anybody knows whether Slicer is able or not to manage >4GB data, or if some optimizations could be required ?

Fabien

-----Message d'origine-----
De : [hidden email] [mailto:[hidden email]] De la part de arumiat
Envoyé : lundi 25 janvier 2016 23:38
À : SPL Slicer Users <[hidden email]>
Objet : [slicer-users] Working with very large datasets

Hi Slicer community,

I've been lucky enough to be passed some very beautiful datasets using the BriteVu contrast agent http://www.scarletimaging.com/ <http://www.scarletimaging.com/>

I'm keen to start working with them but they are extremely large (~5GB), and my system chokes on them, Slicer essentially freezes and I can't do much, and end up having to force quit. This has never happened before, and I'm on a pretty decent spec laptop so I'm a bit surprised..
i7
16GB system RAM
Nvidia 870M w 6GB video RAM
SSD
64GB Windows
Slicer 4.4

Is this a system memory issue? Would upgrading to 32GB RAM help get around this do you think? Any other tips on things I could try?





--
View this message in context: http://slicer-users.65878.n3.nabble.com/Working-with-very-large-datasets-tp4029896.html
Sent from the slicer-users mailing list archive at Nabble.com.
_______________________________________________
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To unsubscribe: send email to [hidden email] with unsubscribe as the subject http://www.slicer.org/slicerWiki/index.php/Documentation/4.3/FAQ


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.
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contains patient information, please contact the Partners Compliance HelpLine at
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Re: Working with very large datasets

Steve Pieper-2
In reply to this post by Fabien PERTUY
Hi Taimur - 

The microCT I'm using came in some proprietary format (.vol / .vgi) so I convert them to nrrd using Slicer and a custom script.  

Compressing the files to jpeg will save you disk space, but they need to be uncompressed in memory in Slicer so that's the real choke point.  Plus any operation in Slicer will require extra buffers, so it end up needing a few times the memory of the source volume.

Yes, ResampleScalarVolume in Slicer can do what you need.  Or CropVolume lets you specify the output spacing so you can do both operations at once.

Externally ifranview has a nice GUI for batch resize that you could apply to tiffs before loading them in Slicer, but it'll be a 2D resize and not as good as doing it in 3D in Slicer.

Best,
Steve

On Tue, Jan 26, 2016 at 10:16 AM, Taimur Alavi <[hidden email]> wrote:
Thanks Steve,

I imagine these files are currently TIFF? Is there a way to batch process them to JPEG-2000 using external software or something?

Is downsampling done via the ResampleScalarVolume?

Thanks,
T

------------------------------------
V A L A design
+ 4 4 (0) 2 0 3 6 3 7 0 0 6 2
IVALA LTD.   REG NO.7931234


On 26 January 2016 at 14:38, Steve Pieper <[hidden email]> wrote:
Hi Guys - 

A lot will depend on the system and what operations you intend to do.  As an example on my mac with 64 gig of ram I can open and view a microCT dataset that is over 10G uncompressed, but most operations are impractical.

There is research on large volume processing being done using the same core infrastructure as Slicer (e.g. running VTK on clusters) but we haven't brought that into the Slicer environment.

For now it's best to downsample or crop to match the hardware you have access to.

Best,
Steve

On Tue, Jan 26, 2016 at 5:26 AM, Fabien PERTUY <[hidden email]> wrote:
Hi,

I had problems using Slicer with 4-8GB datasets as well, but in my case not only the system freezes but it sometime just won't open the file.
As I use a system with similar specs as yours, but more RAM, I would say it is not a RAM issue (at least RAM won't be the only one).

Does anybody knows whether Slicer is able or not to manage >4GB data, or if some optimizations could be required ?

Fabien

-----Message d'origine-----
De : [hidden email] [mailto:[hidden email]] De la part de arumiat
Envoyé : lundi 25 janvier 2016 23:38
À : SPL Slicer Users <[hidden email]>
Objet : [slicer-users] Working with very large datasets

Hi Slicer community,

I've been lucky enough to be passed some very beautiful datasets using the BriteVu contrast agent http://www.scarletimaging.com/ <http://www.scarletimaging.com/>

I'm keen to start working with them but they are extremely large (~5GB), and my system chokes on them, Slicer essentially freezes and I can't do much, and end up having to force quit. This has never happened before, and I'm on a pretty decent spec laptop so I'm a bit surprised..
i7
16GB system RAM
Nvidia 870M w 6GB video RAM
SSD
64GB Windows
Slicer 4.4

Is this a system memory issue? Would upgrading to 32GB RAM help get around this do you think? Any other tips on things I could try?





--
View this message in context: http://slicer-users.65878.n3.nabble.com/Working-with-very-large-datasets-tp4029896.html
Sent from the slicer-users mailing list archive at Nabble.com.
_______________________________________________
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To unsubscribe: send email to [hidden email] with unsubscribe as the subject http://www.slicer.org/slicerWiki/index.php/Documentation/4.3/FAQ


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.
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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
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Re: Working with very large datasets

Murat Maga
In reply to this post by arumiat
Hi Taimur,

>From a non-expert point of view, I use 4-to-1 memory to dataset ratio to decide whether I have enough resources. So if you are using a 5GB dataset on a 16GB computer, you will be pushing hard, especially on windows platform where memory fragmentation is a common. You might get by with manual segmentation, but any kind of filter operation (connected components, smoothing) or registration will most likely fail. Especially if the operations are giving float output.

Assuming you need that high-resolution to see vasculature in detail, either try to crop the FOV and restrict yourself to the region you really need to work at full resolution, or reduce the dataset. You can do this in Slicer (crop volume, resamplescalarvolume) or using Fiji (http://fiji.sc), which unlike Irfanview will interpolate also in Z plane. Fiji version of IJ will read and write nifti and nrrd through bioformats plugin, so it is minimal amount of work to go back and forth with Slicer.

M


-----Original Message-----
From: [hidden email] [mailto:[hidden email]] On Behalf Of arumiat
Sent: Tuesday, January 26, 2016 2:05 AM
To: SPL Slicer Users
Subject: Re: [slicer-users] Working with very large datasets

*From Murat: */Depending on what you are trying to do, you might be running out of memory. Is the dataset 5GB compressed? If so, you are definitely running out of memory.

Again depending on what you want to do 32GB RAM may not resolve your issues.
You may need much more memory. Or you can try to resample (reduce) the volume to make it work within the confines of your memory./

Hi Murat,

Thank you. I'm not sure if it's compressed, is there a way to tell? I just took a look and each individual .dcm file is 2,050KB so I'm thinking it isn't! How would you recommend compressing them all if this is the case?
The aim is to extract 3D models from it of vasculature, so lossless compression would be best.

Are you also able to suggest how to to resample the volume to achieve better performance? The ResampleScalarVolume module?

Thanks in advance,
T



--
View this message in context: http://slicer-users.65878.n3.nabble.com/Working-with-very-large-datasets-tp4029896p4029900.html
Sent from the slicer-users mailing list archive at Nabble.com.
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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.

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Re: Working with very large datasets

arumiat
In reply to this post by arumiat
That's very useful information, thanks all. 

I'd like to be able to use ResampleScalar volume or Crop volume within Slicer but Slicer is basically non-responsive once the data has loaded.

I've downloaded Fiji J Murat. I tried 'Batch' -> 'Convert' function to convert the .dcm files to .tiffs at half scales and that worked, but I couldn't load them into Slicer. Can you point me to which function I need to use to resample them with interpolation in the Z plane as well? Will their output then still be .dcm? Their documentation isn't too enlightening.

Hope to hear, T

------------------------------------
V A L A design
+ 4 4 (0) 2 0 3 6 3 7 0 0 6 2
IVALA LTD.   REG NO.7931234


On 26 January 2016 at 17:07, Murat Maga <[hidden email]> wrote:
Hi Taimur,

>From a non-expert point of view, I use 4-to-1 memory to dataset ratio to decide whether I have enough resources. So if you are using a 5GB dataset on a 16GB computer, you will be pushing hard, especially on windows platform where memory fragmentation is a common. You might get by with manual segmentation, but any kind of filter operation (connected components, smoothing) or registration will most likely fail. Especially if the operations are giving float output.

Assuming you need that high-resolution to see vasculature in detail, either try to crop the FOV and restrict yourself to the region you really need to work at full resolution, or reduce the dataset. You can do this in Slicer (crop volume, resamplescalarvolume) or using Fiji (http://fiji.sc), which unlike Irfanview will interpolate also in Z plane. Fiji version of IJ will read and write nifti and nrrd through bioformats plugin, so it is minimal amount of work to go back and forth with Slicer.

M


-----Original Message-----
From: [hidden email] [mailto:[hidden email]] On Behalf Of arumiat
Sent: Tuesday, January 26, 2016 2:05 AM
To: SPL Slicer Users
Subject: Re: [slicer-users] Working with very large datasets

*From Murat: */Depending on what you are trying to do, you might be running out of memory. Is the dataset 5GB compressed? If so, you are definitely running out of memory.

Again depending on what you want to do 32GB RAM may not resolve your issues.
You may need much more memory. Or you can try to resample (reduce) the volume to make it work within the confines of your memory./

Hi Murat,

Thank you. I'm not sure if it's compressed, is there a way to tell? I just took a look and each individual .dcm file is 2,050KB so I'm thinking it isn't! How would you recommend compressing them all if this is the case?
The aim is to extract 3D models from it of vasculature, so lossless compression would be best.

Are you also able to suggest how to to resample the volume to achieve better performance? The ResampleScalarVolume module?

Thanks in advance,
T



--
View this message in context: http://slicer-users.65878.n3.nabble.com/Working-with-very-large-datasets-tp4029896p4029900.html
Sent from the slicer-users mailing list archive at Nabble.com.
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Re: Working with very large datasets

brhoom
Dear all,
I have the same problem. I tried this:
<SlicerPath>Slicer  --launch
<SlicerPath>/lib/Slicer-4.5/cli-modules/ResampleScalarVolume --spacing
0.1,0.1,0.1 ./mCT1 ./mCT2

but I get this error:
<SlicerPath>/lib/Slicer-4.5/cli-modules/ResampleScalarVolume: exception
caught !
itk::ExceptionObject (0xf72c70)
Location: "unknown"
File:
/home/kitware/Dashboards/Nightly/Slicer-0-build/ITKv4/Modules/IO/PNG/src/itkPNGImageIO.cxx
Line: 107
Description: itk::ERROR: PNGImageIO(0xf6f6d0): PNGImageIO failed to read
header for file:
Reason: fread read only 0 instead of 8

It looks like DICOM is not supported, any suggestion?
Have a nice day!
 



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Re: Working with very large datasets

brhoom
This post has NOT been accepted by the mailing list yet.
In reply to this post by arumiat
Dear all,
I have the same problem. I tried this:
<SlicerPath>Slicer  --launch <SlicerPath>/lib/Slicer-4.5/cli-modules/ResampleScalarVolume --spacing  0.1,0.1,0.1 ./mCT1 ./mCT2

but I get this error:
<SlicerPath>/lib/Slicer-4.5/cli-modules/ResampleScalarVolume: exception caught !
itk::ExceptionObject (0xf72c70)
Location: "unknown"
File: /home/kitware/Dashboards/Nightly/Slicer-0-build/ITKv4/Modules/IO/PNG/src/itkPNGImageIO.cxx
Line: 107
Description: itk::ERROR: PNGImageIO(0xf6f6d0): PNGImageIO failed to read header for file:
Reason: fread read only 0 instead of 8

It looks like DICOM is not supported, any suggestion?
Have a nice day!
 
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Re: Working with very large datasets

Andras Lasso-2
In reply to this post by brhoom
I don't think CLIs can work directly with DICOM files. ITK file IO may be able to open DICOM image files in some cases, but in general correctly reading DICOM data is a complex task. Just an example: typically you get a directory that contains several directories and thousands of files - how would you even know which one file to pass to your CLI?

You can see an example of batch processing of DICOM files using Slicer at the link Csaba sent yesterday:

https://github.com/SlicerRt/SlicerRT/blob/master/BatchProcessing

Andras

-----Original Message-----
From: slicer-users [mailto:[hidden email]] On Behalf Of brhoom
Sent: December 8, 2016 4:46
To: SPL Slicer Users <[hidden email]>
Subject: Re: [slicer-users] Working with very large datasets

Dear all,
I have the same problem. I tried this:
<SlicerPath>Slicer  --launch
<SlicerPath>/lib/Slicer-4.5/cli-modules/ResampleScalarVolume --spacing
0.1,0.1,0.1 ./mCT1 ./mCT2

but I get this error:
<SlicerPath>/lib/Slicer-4.5/cli-modules/ResampleScalarVolume: exception caught !
itk::ExceptionObject (0xf72c70)
Location: "unknown"
File:
/home/kitware/Dashboards/Nightly/Slicer-0-build/ITKv4/Modules/IO/PNG/src/itkPNGImageIO.cxx
Line: 107
Description: itk::ERROR: PNGImageIO(0xf6f6d0): PNGImageIO failed to read header for file:
Reason: fread read only 0 instead of 8

It looks like DICOM is not supported, any suggestion?
Have a nice day!
 



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