Joshua Kaggie

Researcher

Department of Radiology

About Joshua Kaggie

Hello! I’m Joshua Kaggie, an MRI Physicist and Assistant Research Professor in the Department of Radiology at the University of Cambridge, where I’ve been based since 2015. Originally from the United States, I earned my PhD in MRI methods at the University of Utah, focusing on cutting-edge MRI hardware and imaging techniques – mostly developing radiofrequency coils/methods for sodium MRI in the breast. Now, in Cambridge, I’m pushing the boundaries of medical imaging to improve diagnostics and patient care. 

My work revolves around developing faster, more sensitive MRI methods to unlock new possibilities in clinical and research settings. I’m particularly excited about three areas: 

  1. MRI physics, such as MRI fingerprinting and advanced physics simulations and image reconstruction to speed up scans without sacrificing quality
  2. X-nuclei MRI, imaging non-hydrogen atoms like sodium or carbon to reveal unique biochemical insights
  3. and machine learning, where I’ve contributed to automated techniques for analysing tissues, such as identifying knee cartilage in MRI scans

My research spans cancer, osteoarthritis, and other diseases, with projects like sodium MRI for breast cancer imaging and hyperpolarised carbon-13 MRI for imaging metabolism in vivo. 

Beyond the lab, I enjoy sharing my work through public talks—like discussing the role of light in medical imaging at the Cambridge Festival or exploring AI’s potential at the Festival of Genomics. I also serve as a Category Chair for the European Molecular Imaging Meeting 2025 and regularly review for journals like Magnetic Resonance in Medicine. 

When I’m not immersed in MRI physics, you might find me marvelling at Cambridge’s historic charm. I’m always eager to connect with prospective PhD students or collaborators who share a curiosity for advancing medical imaging. Feel free to reach out!

Project/study information

My projects include: hyperpolarised xenon for lung imaging, imaging deuterium metabolism (particularly in the abdomen), and sodium MRI for breast cancer. My work also includes machine learning for super-resolution, denoising, and evaluation, plus brain aneurysm imaging and federated learning. 

Looking for a supervisee

I’m actively recruiting PhD students – about one per year – and occasionally postdocs to join my team at the University of Cambridge’s Department of Radiology. Students should have a relevant background – although many backgrounds can be considered if the case can be made. This will generally be in physics, engineering, or computer science. Contact me by email if interested.