Outline

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Outline

• Introduction
• Image Registration
• High Performance Computing
• Desired Testing Methodology
• Reviewed Registration Methods
• Preliminary Results
• Future Work
• Cool App Demo

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Introduction

• Primary Motivation
• After some research, the scope of this project
  increased tenfold

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Image Registration

• Image Registration is the process of determining
  a spatial transformation that establishes the
  correspondence of two images

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Image Registration

• Applications of Image Registration
• Cartography
• Computer Vision
• Image Guided Surgery
• Brain Mapping
• Detection of Disease state change over time
• And many more

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Image Registration

• Software packages, libraries, and frameworks
  capable of Image Registration
• Automated Image Registration Package (AIR)
• Insight Segmentation and Registration Toolkit
  (ITK)
• FLexible Image Registration Toolkit (FLIRT)
• Mathworks Image Processing Toolkit
• Others
• None currently support registration by means of
  parallel computing!

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Image Registration

• Depending on the application, registration can be
  highly demanding of resources
• Large amounts of data to be worked on can be too
  large for physical memory (results in disk
  swapping)
• Search spaces (deformable problems can get as
  large as say 9.8 106)

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High Performance Computing

• Extremely efficient in reducing performance and
  memory issues
• Steadily decreasing prices and a high increase
  availability of high performance machines has
  made parallel computing for many a reality
• Most image registration specialists are not
  familiar with parallel and distributed computing
  techniques
• Many researchers have successfully applied such
  methods, but none have a created a generic
  software module

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High Performance Computing

• My Role
• Administer and maintain the two clusters Nick and
  Optimus
• Head of the USC High Performance Computing Group
• Assist users
• Developed and (try to) maintain the HPCG Webpage

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High Performance Computing

• Systems Nick
• HARDWARE 76 Compute Nodes Dual 3.4 Xeon 2ML2,
  4GB RAM, 1-40GB1 Master Node Dual 3.2 GHz Xeon
  2ML2, 4GB RAM, 3-73GB disks RAID 5
• INTERCONNECT Topspin Infiniband
• SOFTWARE Platform Rocks 4 (RHEL 4), Platform
  LSF, OpenMPI (Compiled with Infiniband
  Libraries), 64bit GCC compiles, Intel Compilers,
  Star-CD, ITK, others
• Will support starting Summer GAMESS, NWCHEM,

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High Performance Computing

• Systems Optimus
• HARDWARE 64 Compute Nodes Dual, Dual-core 2.2
  GHz Opteron 2ML2, 8GB RAM, 1-250GB1 Master Node
  Dual, Dual-core 2.2 GHz Xeon 2ML2, 8GB RAM,
  2-500GB disks
• INTERCONNECT GigE
• SOFTWARE Fedora Core 4, ABC Management Software,
  OpenPBS scheduling software. OpenMPI (Compiled
  with Infiniban Libraries), 64bit GCC compiles,
  Intel Compilers, ITK, others
• Will support starting Summer GAMESS, NWCHEM,

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High Performance Computing

• Message Passing
• In distributed memory systems, the most prevalent
  means of communication is message passing
• Message Passing Interface (MPI)
• Takes care of low-level details such as
  buffering, error handling, and data-type
  conversion
• Middleware component in conjunction with standard
  programming language like C, C, and Fortran

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High Performance Computing

• Issues with Multi-core 6
• Memory Contention
• Interconnect Contention
• Program Locality
• "--mca mpi_paffinity_alone 1"

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Desired Testing Methodology

• Research and analyze existing registration
  frameworks to determine if their workload can be
  distributed in a parallel environment
• Thoroughly test all methods sequentially and in
  parallel to determine Speedup
• Testing in 2-D and 3-D, intermodal and
  intramodal, and rigid and non-rigid image
  registration
• Focus on Intensity based methods
• Address known multi-core issues

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Desired Testing Methodology

• Two strategies
• Parallelizing the optimization method
• Parallelizing the metric function

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Desired Testing Methodology

• The measure of quality will be defined using
  Parallel Speedup and Parallel Efficiency
• Parallel speed up is defined as
• SN TS/TN
• where TS is the execution time of the best
  sequential algorithm, and TN is the execution
  time on N processors
• Parallel efficiency is defined as
• EN SN/N
• where N is the number of processors

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Reviewed Registration Methods

• Warfields Approach 3
• Cachier's demons algorithm 5 as used in 7
• Claims its precise, robust, relatively low
  computation time
• Structure makes it a good candidate for
  parallelization
• Can be divided into three main bricks
• Oversampling needed by the pyramidal approach
• Search for the matches
• Parallel gaussian filtering

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Reviewed Registration Methods

• Cachier's demons algorithm 5 as used in 6

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Reviewed Registration Methods

• Acceleration of Genetic Algorithm with Parallel
  Processing with Application in Medical Image
  Registration (B. Laksanapanai W.
  Withayachumnankul C. Pintavirooj P.Tosranon)
• Very intriguing, but such a short paper and
  didnt really dive into how it was implemented

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Reviewed Registration Methods

• Distributed Registration Framework as proposed by
  Michael Kuhn 1
• The metric calculation is organized in a
  master/slave design.
• The master process is responsible for data
  distribution as well as communication of the
  existing framework
• Each slave is assigned a region of the fixed
  image, and calculates an intermediate metric
  value
• Master node coordinates all steps required to
  collect and process the partial results and
  passes the final result to the registration
  framework

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Reviewed Registration Methods
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Reviewed Registration Methods

• Implemented these concepts through
• DistributedImageToImageMetric
• RegistrationCommunicator
• DistributedImageToImageMetric class is divided
  into master and slave, and is derived from
  itkImageToImageMetric class
• RegistrationCommuncator provides an interface for
  all communication tasks and uses MPI

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Reviewed Registration Methods

• Whole registration process consists of two
  stages Initialization and Optimization
• Initialization distribute data to nodes
• Optimization optimizers in ITK work iteration
  based
• During each iteration, metric values and
  derivatives are requested from metric function
• When new values are required, optimizer requests
  a metric from the master, master then asks slaves
  to compute the partial value associated with
  their fixed region and transmits back to master
• Master processes and repeats until complete

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Preliminary Results

• Sequential Runs MeanSquaresImagetoImageMetric

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Preliminary Results

• Sequential Runs MeanSquaresImagetoImageMetric

Nick Optimus
Best Run Time 427.7 s 522.3 s
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Future Work

• Implement an attachable parallel image
  registration framework (that supports Multi-core
  as well) to existing tools such as ITK
• Thorough Testing on both clusters
• The usage of multiple cores in one node requires
  a new programming model
• Forms of Data Decomposition

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• Questions?

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• Photosynth Demo