Enhancing Ultra-Low-Dose PET/MRI Using Deep Learning Method for Improved Interpretation
Motivation: We developed a deep learning model to enhance the image quality of ultra-low dose brain PET. Goal(s): Significantly reducing the injected dose not only minimizes radiation risk in subjects but also provides options for scanning protocols, and more follow-up studies. Approach: We proposed a 3D-Residual Attention U-Net model initially trained on whole-body [18F]FDG PET/MR images. We used transfer learning approach to fine-tune our proposed model on [18F]CPFPX PET/MRI inhouse dataset. Results: We achieved improved metrics compared to U-Net model with average PSNR of 28.02 (U-Net: 21.23), SSIM of 0.81 (U-Net: 0.53), CNR of 0.72 (U-Net: 0.61) and NMSE of 0.33 (U-Net: 0.67). Impact: Our model has potential to generate high-quality PET images from low-dose PET/MR, potentially contribute to implementation of kinetic modelling using PET/MR imaging. Our model is capable of enhancing both whole-body and brain datasets, making it valuable asset for diverse applications.
Authors
- Denise Lange (ORCID: https://orcid.org/0000-0002-0853-1987)
- Simone Beer (ORCID: https://orcid.org/0000-0003-4290-4051)
- Tina Kroll (ORCID: https://orcid.org/0000-0002-5814-8601)
- David Elmenhorst (ORCID: https://orcid.org/0000-0001-6137-416X)
- Hans‐Peter Landolt (ORCID: https://orcid.org/0000-0003-0887-9403)
- Eva Hennecke (ORCID: https://orcid.org/0000-0002-7717-8937)
- Daniel Aeschbach (ORCID: https://orcid.org/0000-0002-6054-5753)
- Diego M. Baur (ORCID: https://orcid.org/0000-0002-1486-3603)
- Anum Masood (ORCID: https://orcid.org/0000-0001-5411-8969)
- Bernd Neumaier (ORCID: https://orcid.org/0000-0001-5425-3116)
- Anna L. Foerges (ORCID: https://orcid.org/0000-0003-1322-0291)
- Alexander Drzezga (ORCID: https://orcid.org/0000-0001-6018-716X)
- Andreas Bauer (ORCID: https://orcid.org/0000-0002-7681-3177)
- Eva-Maria Elmenhorst
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/1977
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00