United Imaging Healthcare Enhanced the Speed and Quality of MR Imaging
United Imaging Healthcare· ChinaNVIDIA data center GPUs · NVIDIA CUDA Toolkit · NVIDIA cuSolver +1
United Imaging Healthcare worked with NVIDIA since 2018 to accelerate its magnetic resonance (MR) imaging products with AI, developing an AI-assisted compressed sensing (ACS) technology to speed up MR image acquisition and reconstruction. Using NVIDIA data center GPUs, the CUDA Toolkit, cuSolver matrix computation library, and NVIDIA AI Enterprise software (with support from NVIDIA DevTech engineers and solution architects), United Imaging Healthcare reduced image reconstruction time by nearly 95%, with NVIDIA's support teams further accelerating algorithms by an additional 3x, on top of an initial 10x increase in computational speed from a tailored algorithm.
Overview
United Imaging Healthcare worked with NVIDIA since 2018 to accelerate its magnetic resonance (MR) imaging products with AI, developing an AI-assisted compressed sensing (ACS) technology to speed up MR image acquisition and reconstruction. Using NVIDIA data center GPUs, the CUDA Toolkit, cuSolver matrix computation library, and NVIDIA AI Enterprise software (with support from NVIDIA DevTech engineers and solution architects), United Imaging Healthcare reduced image reconstruction time by nearly 95%, with NVIDIA's support teams further accelerating algorithms by an additional 3x, on top of an initial 10x increase in computational speed from a tailored algorithm.
The challenge
Reconstructing high-quality MR images requires extremely compute-intensive workloads, and the company needed to leverage more streaming sensor data to achieve higher throughput in less time; even with proprietary algorithms, processing streaming sensor data still took too much time and expense to meet the needs of clinicians.
The solution
Since 2018, United Imaging Healthcare has worked with NVIDIA to accelerate its MR imaging products with AI, developing AI-assisted compressed sensing (ACS) technology to speed up MR image acquisition and reconstruction. The team used NVIDIA data center GPUs, the CUDA Toolkit, the cuSolver matrix computation library, and NVIDIA AI Enterprise software, with support from NVIDIA DevTech engineers and solution architects who helped train models, analyze code, and migrate to GPUs; NVIDIA engineers also tailored an algorithm that increased computational speed by more than 10x.
Reported business value
United Imaging Healthcare reduced image reconstruction time by nearly 95%, with NVIDIA's support teams further accelerating algorithms by an additional 3x, on top of an initial 10x increase in computational speed from the tailored algorithm. Clinical teams can now limit the amount of time patients spend in constrained MR machines, and hospitals can increase access to MR procedures.
Sources
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