Fast GPU 3D diffeomorphic image registration

Brunn, Malte; Himthani, Naveen; Biros, George; Mehl, Miriam; Mang, Andreas

doi:10.1016/j.jpdc.2020.11.006

Fast GPU 3D diffeomorphic image registration

Journal Article · Thu Dec 10 00:00:00 EST 2020 · Journal of Parallel and Distributed Computing

DOI:https://doi.org/10.1016/j.jpdc.2020.11.006· OSTI ID:1850434

Brunn, Malte ^[1]; Himthani, Naveen ^[2]; Biros, George ^[2]; Mehl, Miriam ^[3]; Mang, Andreas ^[4]

Univ. of Stuttgart (Germany); Univ. of Stuttgart (Germany)
Univ. of Texas, Austin, TX (United States)
Univ. of Stuttgart (Germany)
Univ. of Houston, TX (United States)

3D image registration is one of the most fundamental and computationally expensive operations in medical image analysis. Here, we present a mixed-precision, Gauss–Newton–Krylov solver for diffeomorphic registration of two images. Our work extends the publicly available CLAIRE library to GPU architectures. Despite the importance of image registration, only a few implementations of large deformation diffeomorphic registration packages support GPUs. Our contributions are new algorithms to significantly reduce the run time of the two main computational kernels in CLAIRE: calculation of derivatives and scattered-data interpolation. Additionally, we deploy (i) highly-optimized, mixed-precision GPU-kernels for the evaluation of scattered-data interpolation, (ii) replace Fast-Fourier-Transform (FFT)-based first-order derivatives with optimized 8th-order finite differences, and (iii) compare with state-of-the-art CPU and GPU implementations. As a highlight, we demonstrate that we can register clinical images in less than 6 s on a single NVIDIA Tesla V100. This amounts to over 20 speed-up over the current version of CLAIRE and over 30 speed-up over existing GPU implementations.

View Accepted Manuscript (DOE)

Research Organization:: Duke Univ., Durham, NC (United States); Univ. of Texas, Austin, TX (United States)

Sponsoring Organization:: National Institutes of Health (NIH); National Science Foundation (NSF); US Air Force Office of Scientific Research (AFOSR); USDOE; USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: NA0003969; SC0019393

OSTI ID:: 1850434

Alternate ID(s):: OSTI ID: 1874748

Journal Information:: Journal of Parallel and Distributed Computing, Journal Name: Journal of Parallel and Distributed Computing Journal Issue: C Vol. 149; ISSN 0743-7315

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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