TL;DR
mach is an open-source GPU-accelerated ultrasound beamformer that achieves over 10 times faster processing than existing solutions, enabling real-time 3D ultrafast ultrasound on consumer hardware.
Contribution
The paper introduces mach, a highly optimized GPU-based beamformer with a hybrid delay computation strategy, significantly improving speed and enabling real-time volumetric ultrasound imaging.
Findings
mach processes 1.1 trillion points per second on a consumer GPU.
mach completes reconstruction in 0.23 ms on the PyMUST dataset.
Validation shows errors below -60 dB for Power Doppler and -120 dB for B-mode.
Abstract
Purpose: Volumetric ultrafast ultrasound produces massive datasets with high frame rates, dense reconstruction grids, and large channel counts. Beamforming computational demands limit research throughput and prevent real-time applications in emerging modalities such as elastography, functional neuroimaging, and microscopy. Approach: We developed mach, an open-source, GPU-accelerated beamformer with a highly optimized delay-and-sum CUDA kernel and an accessible Python interface. mach uses a hybrid delay computation strategy that substantially reduces memory overhead compared to fully precomputed approaches. The CUDA implementation optimizes memory layout for coalesced access and reuses delay computations across frames via shared memory. We benchmarked mach on the PyMUST rotating disk dataset and validated numerical accuracy against existing open-source beamformers. Results:…
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