| Title: | Data-driven fast and high-quality MRI |
| Lead Institution: | Imperial College London |
| Principal investigator: |
Application 100203
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About
Project Aim: The goal of this project is to reduce the time required for magnetic resonance imaging (MRI) scans while also improving the image quality. The goal is to make the process more efficient and pleasant for patients while retaining key clinical imaging features. Scientific Importance: The recent advancement of artificial intelligence (AI) in medical imaging is being applied to a variety of clinical data, including MRI scans. The project's goal is to use this technology to create clinically deployable tools for super-resolution (improving spatial resolution) and reconstruction (creating viewable images), which will improve the accuracy and reliability of the results. Project Duration: 36 months Public Health Benefits: The project will take 36 months to complete and will involve further improving the methodology as well as computational and clinical validation of the results. The hope is that this work will boost clinical team confidence in the images generated, resulting in more widespread use of these tools in standard clinical practise. This project is expected to improve patient care by reducing scanning time and allowing for greater access to MRI scans. Imaging quality advancements will also reduce artefacts and provide more detailed information for clinical interpretation, resulting in a tangible impact on the public healthcare system.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 17652 | Explicit differentiable slicing and global deformation for cardiac mesh reconstruction | Yihao Luo (+12) | 2026 | Medical Image Analysis |
Enabling scientific discoveries that improve human health