GPU-based stochastic-gradient optimization for non-rigid medical image registration in time-critical applications

GPU-based stochastic-gradient optimization for non-rigid medical image registration in time-critical applications

Bhosale, P.S. (Leiden University Medical Center)
Staring, M. (TU Delft Pattern Recognition and Bioinformatics; Leiden University Medical Center)
Al-Ars, Z. (TU Delft Computer Engineering)
Berendsen, Floris F. (Leiden University Medical Center)

Angelini, Elsa D. (editor)
Landman, Bennett A. (editor)

2018

Currently, non-rigid image registration algorithms are too computationally intensive to use in time-critical applications. Existing implementations that focus on speed typically address this by either parallelization on GPU-hardware, or by introducing methodically novel techniques into CPU-oriented algorithms. Stochastic gradient descent (SGD) optimization and variations thereof have proven to drastically reduce the computational burden for CPU-based image registration, but have not been successfully applied in GPU hardware due to its stochastic nature. This paper proposes 1) NiftyRegSGD, a SGD optimization for the GPU-based image registration tool NiftyReg, 2) random chunk sampler, a new random sampling strategy that better utilizes the memory bandwidth of GPU hardware. Experiments have been performed on 3D lung CT data of 19 patients, which compared NiftyRegSGD (with and without random chunk sampler) with CPU-based elastix Fast Adaptive SGD (FASGD) and NiftyReg. The registration runtime was 21.5s, 4.4s and 2.8s for elastix-FASGD, NiftyRegSGD without, and NiftyRegSGD with random chunk sampling, respectively, while similar accuracy was obtained. Our method is publicly available at https://github.com/SuperElastix/NiftyRegSGD.

GPGPU
memory access optimization
Non-rigid image registration
random chunk sampling
stochastic gradient descent

http://resolver.tudelft.nl/uuid:611c4637-6acc-4812-b5f1-8cd66530b0fa

https://doi.org/10.1117/12.2293098

SPIE, Bellingham, WA

9781510616370

Medical Imaging 2018: Image Processing

Medical Imaging 2018: Ultrasonic Imaging and Tomography, 2018-02-10 → 2018-02-15, Houston, United States

Proceedings of SPIE, 0277-786X, 10574

Institutional Repository

conference paper

© 2018 P.S. Bhosale, M. Staring, Z. Al-Ars, Floris F. Berendsen