Stride: a flexible platform for high-performance ultrasound computed tomography
Abstract
Advanced ultrasound computed tomography techniques like full-waveform inversion are mathematically challenging and orders of magnitude more computationally expensive than conventional ultrasound imaging methods. This computational and algorithmic complexity, and a lack of open-source libraries in this field, represent a barrier preventing the generalised adoption of these techniques, slowing the pace of research and hindering reproducibility. Consequently, we have developed Stride, an open-source Python library for the solution of large-scale ultrasound tomography problems. On one hand, Stride provides high-level interfaces and tools for expressing the types of optimisation problems encountered in medical ultrasound tomography. On the other, these high-level abstractions seamlessly integrate with high-performance wave-equation solvers and with scalable parallelisation routines. The wave-equation solvers are generated automatically using Devito, a domain specific language, and the parallelisation routines are provided through the custom actor-based library Mosaic. Through a series of examples, we show how Stride can handle realistic tomographic problems, in 2D and 3D, providing intuitive and flexible interfaces that scale from a local multi-processing environment to a multi-node high-performance cluster.
- Publication:
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arXiv e-prints
- Pub Date:
- October 2021
- DOI:
- 10.48550/arXiv.2110.03345
- arXiv:
- arXiv:2110.03345
- Bibcode:
- 2021arXiv211003345C
- Keywords:
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- Physics - Medical Physics;
- Electrical Engineering and Systems Science - Signal Processing;
- Physics - Applied Physics;
- Physics - Computational Physics
- E-Print:
- Computer Methods and Programs in Biomedicine, 221, 2022