[Insight-developers] Streaming and minipipelines

[Jim Miller]

Cory, 

As Brad points out your outer filter is responsible for establishing the proper requested regions for the internal filters. You can either hand code what the complete requested region should be for the mini-pipeline, or you can instantiate a mini-pipeline in the GenerateInputRequestedRegion and ask it for the requested region it needs.  What you don't want to do is wait for the GenerateData() method for the mini-pipeline to put in a "different" request. That may cause the filters above it to executed a second time. This is one of Brad's points.

The localinput pattern that Brad provides is a good way to insulate the mini-pipeline from the outer pipeline. This was needed in the DiscreteGaussian filter as it internally streams a mini-pipeline. Here, the filter asks for the output requested region padded by the kernel size. But internally to GenerateData, we use the streaming mechanism to divide the processing through the mini-pipeline.  This is to limit the amount of memory used to blur a volume while allowing the intermediate voumes to be floating point precision.  Without the localinput pattern, the streaming of the mini-pipeline internally to the GenerateData method would cause the input to the DiscreteGaussian to be Modified whenever a RequestedRegion was established. This would cause future re-rexecutions of the DiscreteGaussian that were unnecessary.

Jim

On Jul 14, 2011, at 10:33 AM, Bradley Lowekamp wrote:

> Hello Cory,
> 
> Currently best documentation on streaming is section 13.3 of the Software Guide and your text editor with the core pipeline objects open, and a good streaming filter.
> 
> Streaming a mini-pipeline is a little clunky. With this filter currently there are a couple subtle issues that can cause excess pipeline execution. Streaming correctly is not only compute the correct output, but also no causing the upstream filters to execute extra-times that aren't needed, or other extra computation. In generally when you are streaming you have very large images, this extra computation is not productive. As your filter currently is, this may occur.
> 
> The following is what I think is the preferred way for mini-pipelines.
> 
> In GenerateInputRequestedRegion() compute exactly what the RR's for the mini-pipeline will be and set the input images to that. 
> 
> In the generate data method, insulate the mini-pipline from being connected to the exterior pipeline with a graft:
> 
>  // Create an internal image to protect the input image's metdata
>  // (e.g. RequestedRegion). The StreamingImageFilter changes the
>  // requested region as part of its normal processing.
>  typename TInputImage::Pointer localInput = TInputImage::New();
>  localInput->Graft( this->GetInput() );
> 
> by doing this you will minimize chatter in the pipeline and subtle bugs will be readily apparent.
> 
> 
> For your case, for input1 you want to mimic itk::DiscreteGaussianImage::GenerateInputRequestedRegion. then add setting the kernel input to the largest possible region ( DataObject::SetRequestedRegionToLargestPossibleRegion ).
> 
> 
> 
> On Jul 14, 2011, at 9:36 AM, Cory Quammen wrote:
> 
>> Dear streaming experts,
>> 
>> I am working on a filter with a minipipeline (ConvolutionImageFilter),
>> and I want to make sure it supports streaming. For a given output
>> request region, this filter needs to request a slightly larger input
>> region from the image input and the largest possible region from the
>> kernel image input.
>> 
>> Now, assuming all the filters in the minipipeline support streaming,
>> what should ConvolutionImageFilter::GenerateInputRequestedRegion() do?
>> It seems to me that the minipipeline filters will handle generating
>> the proper regions in the input for a given requested output region.
>> If I do not override GenerateInputRequestedRegion(), my tests fail.
>> However, if I do override GenerateInputRequestedRegion() and set the
>> input requested regions for both inputs (image and kernel image) to
>> have zero size, everything seems to work.
>> 
>> If there is a presentation or wiki page on the particulars of
>> streaming involving filters with minipipelines, I'm happy to be told
>> to go read that. A few minutes of Googling didn't reveal anything.
>> 
>> Thanks much!
>> Cory
>> 
>> -- 
>> Cory Quammen
>> Research Associate
>> Department of Computer Science
>> University of North Carolina at Chapel Hill
>> http://www.cs.unc.edu/~cquammen
> 

Jim Miller
Senior Scientist
GE Research 
Interventional and Therapy

GE imagination at work

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