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SU-E-J-91: FFT Based Medical Image Registration Using a Graphics Processing Unit (GPU).

J Luce¹, M Hoggarth¹, J Lin¹

¹Loyola University Medical Center, Maywood, IL.

Medical Physics

|May 19, 2017

Summary

This summary is machine-generated.

Graphics Processing Units (GPUs) significantly accelerate Fourier Transform (FT) image registration. This GPU acceleration offers near real-time, sub-pixel image alignment capabilities, improving computational efficiency.

Keywords:

Fourier analysis Fourier transforms Image analysis Image registration Medical imaging

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Area of Science:

Medical Imaging
Computational Science

Background:

Fourier Transform (FT) based image registration is crucial for aligning images.
Achieving sub-pixel resolution in FT registration requires image enlargement, increasing computational cost.
Graphics Processing Units (GPUs) offer parallel processing capabilities that can potentially reduce computational time.

Purpose of the Study:

To quantify the efficiency gains of using a GPU for FT-based image registration.
To evaluate the speedup achieved by GPU acceleration compared to Central Processor Unit (CPU) computation.

Main Methods:

Implemented FT image registration algorithm using Interactive Data Language (IDL).
Developed both CPU-based and GPU-accelerated versions of the algorithm.
Benchmarked computational times for various image sizes (256x256 to 2304x2304) on the same system.

Main Results:

GPU computation was consistently faster than CPU computation across all tested image sizes (CPU-to-GPU time ratio > 1.0).
Speedup increased with image size, ranging from 1.21 for 256x256 images to 4.25 for 2304x2304 images.

Conclusions:

GPU implementation significantly reduces computational time for FT image registration.
This GPU acceleration enables near real-time, sub-pixel image registration.