Innovation Spotlight: Finding new ways of enhancing magnetic resonance imaging
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- Nov 26, 2025
- 5 minute read
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In 1973, Nottingham University physicist, Sir Peter Mansfield, first harnessed nuclear magnetic resonance to create cross-sectional images of living tissue. This was the beginning of a revolution in medical diagnosis: magnetic resonance imaging (MRI).
Now, with over 60 million scans conducted in hospitals around the world each year, MRI technology remains the gold standard for soft tissue imaging, used extensively for diagnosing and treating various health conditions. At Philips, we have been continuously innovating this life-saving technology, finding new ways to enhance imaging through artificial intelligence (AI) enablement and leveraging data use.
At the forefront of MRI innovations in Philips are Yolanda Noorda and Kirsten Koolstra, MRI Reconstruction Algorithm Developers, transforming data into images through algorithms that enhance medical imaging to speed up time to diagnosis. Let’s find out about their incredible work and the role they’ve played in helping to revolutionize MRI technology.
Tell us about the work you do in MRI reconstruction. What is it, and how has AI changed the game?
Kirsten: When a patient is lying in the scanner, the magnetic coils that surround them generate a signal, which gives us the information we need to reconstruct a diagnostic image. The problem is, MRI generates a lot of noise and artifacts, too. Our task is to “denoise” MRI images: i.e., filter noise out to only focus on the clinically useful data underneath so that we get accurate, high-quality images – quickly.
Yolanda: For example, our MRI SmartSpeed software uses Adaptive-CS-Net, an AI reconstruction algorithm to accelerate MRI scans. By applying AI algorithms during image reconstruction, it achieves up to 65% greater resolution* and up to 50% shorter exam times†. SmartSpeed also enables us to leverage all the scan data to denoise the image as soon as possible in the reconstruction process, creating a better-quality image faster than before – going beyond what classical reconstruction techniques can do.
Kirsten: We train our algorithms to split the noise from the signal by detecting which is which. We apply this learning to newly seen scan data, improving image quality and decreasing scan time. However, developing an algorithm is just the start of our product development. To get it ready for market, we need to standardize it for usefulness across different clinical applications, ensure stability and safety through rigorous testing, and design the product to optimize user-friendliness.
Why is reducing scan time so important?
Yolanda: MRI is a slow process, so innovation that speeds it up is crucial. Some complex scans can easily take up to 45 minutes. Reducing this means patients spend less time laying still in the scanner, and more patients can have access to the technology. Just recently, we showcased the latest release on the software, SmartSpeed Precise, at the European Congress of Radiology (ECR). This development further reduces scan times and improves diagnostic image quality, extending AI-driven efficiency across the entire Philips MR portfolio.
*Compared to Philips SENSE imaging.
† Compared to Philips scans without Compressed SENSE.
“The opinions and clinical experiences presented herein are specific to the featured article and are for information purposes only. The results from and experiences may not be predictive of all patients. Individual results may vary depending on a variety of patient-specific attributes and related factors. Nothing in this presentation is intended to provide specific medical advice or to take the place of written law or regulations.”
Sources
- *Compared to Philips SENSE imaging.
- † Compared to Philips scans without Compressed SENSE.