High Performance Deformable Image Registration Algorithms for Manycore Processors

By

  • James Shackleford, Assistant Professor, Drexel University ECE Dept.
  • Nagarajan Kandasamy, Drexel University, Philadelphia, PA, USA
  • Gregory Sharp, Massachusetts General Hospital, Boston, MA, USA

High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. Extracting useful information from 2D/3D data is essential to realizing key technologies underlying our daily lives. Examples include autonomous vehicles and humanoid robots that can recognize and manipulate objects in cluttered environments using stereo vision and laser sensing and medical imaging to localize and diagnose tumors in internal organs using data captured by CT/MRI scans.
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Audience

Developers of image registration algorithms and software, including graduate students, researchers (post-doctoral researchers, research scientists, professionals working in the areas of computer vision, image processing, and medical imaging.

 

Book information

  • Published: July 2013
  • Imprint: MORGAN KAUFMANN
  • ISBN: 978-0-12-407741-6

Reviews

"Shackleford, Kandasamy and Sharp develop highly data-parallel deformable image registration algorithms suitable for use on modern multicore processors. Their grid alignment technique and associated data structures reduce the complexity of B-spline registration and can be extended to perform multimodal image registration by utilizing the mutual information similarity metric."--Reference & Research Book News, October 2013




Table of Contents

1. Introduction

2. Overview of Image Registration Algorithms

3. Deformable Registration using Optical Flow Methods

4. Uni-Modal B-spline Registration

5. Multi-Modal B-spline Registration

6. Analytic Vector Field Regularization

7. Plastimatch – An Open Source Software Suite for Image Reconstruction and Registration