YuTing Chen Young kyu Choi Jason Cong and Bingjun Xiao Center for DomainSpecific Computing Center for Future Architectures Research Computer Science Department UCLA ID: 675502
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Slide1
Medical Imaging Pipeline
Yu-Ting Chen, Young-kyu Choi, Jason Cong, and Bingjun XiaoCenter for Domain-Specific ComputingCenter for Future Architectures ResearchComputer Science Department, UCLASlide2
Medical Imaging Pipeline
3D imagesMajor Steps:Imaging reconstructionDenoise/deblurImage registrationImage reconstructionSlide3
Reconstruction
DenoiseRegistrationSegmentationData access patternRandom in EMupdate
Stencil in TVupdateStencilRandom in interp;Stencil in othersStencilMajor computation
FP(
mul
, add)
FP(
mul, add, div, sqrt)FP(mul, add)FP(mul, add, div, sqrt)
Summary of Application Characteristics
3D images
Data access
pattens
Most of the applications contain stencil computation
Some of them has random access
pattens
Floating point computations
Add, multiplication, division,
sqrtSlide4
Image Reconstruction
Forward & Backward Projection
Coordinate & intersection length computation :
Do projection based on the updated images
Update images (voxels)Slide5
Remove noises which under Rician distribution
Solve the minimization problem using gradient decentIterative optimization (nested loop)Stencil computationHardware opt. techniquesTilingData reuse designPipeliningDenoiseSlide6
Registration: fluid registration
Align two images and capture the tumorsFluid PDE equationupdateU / update – stencil; updateV - sweepingSegmentation:Try to find and segment an object of interestgradient decent: stencil computationStencil computation patternsApply similar techniques using in DenoiseRegistration & Segmentation
Dataflow of registrationSlide7
Backup SlidesSlide8
Mapping to FPGA Architecture