Siemens adds deep learning to maintain image quality during faster MR scanning

The quality of MR imaging is defined by the trade-off between scan time, resolution and image noise. Improving one of these parameters usually requires compromising on one of the others. Deep Resolve, a deep learning solution for image reconstruction from Siemens Healthineers, is designed to eliminate this dilemma. The company says it enables clinicians to choose a significantly faster scan time while reducing noise and keeping the same resolution or even increasing image quality.

Deep Resolve has potential to shorten scan times from the first step of image creation with all the available raw data. Its algorithms can therefore speed up scan times for brain MRI by up to 70 per cent while doubling resolution. Adding Simultaneous Multi-Slice (SMS) technology from Siemens Healthineers can accelerate scan time further, by up to 80 per cent.

“We can enable our customers in the NHS and private healthcare organisations to use their scanners in ways we have not seen before,” said Siemens Healthineers GB&I magnetic resonance business manager Alistair Piggot. “Knee imaging in MRI usually takes about 10 minutes on a 3.0T system. Using Deep Resolve algorithms, we got that time down to under two minutes, with the same image quality and diagnostic value.”

Picture: Highly accelerated MR acquisitions can result in strong noise contamination when using conventional reconstruction. With Deep Resolve, high acceleration factors can be applied, with consistent image quality.

See the full report on page 23 of the August 2022 issue of RAD Magazine.

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