Despite these extraordinary times normal research activities continue, which for the Computational Collaborative Project (CCP) PET-MR includes transitioning to the Collaborative Computational Project on Synergistic Reconstruction for Biomedical Imaging (CCP SyneRBI). Led by Prof. Kris Thielemans of UCL, with partners: Andrew Reader (KCL), Charalampos Tsoumpas (UoLeeds), David Atkinson (UCL), Julian Matthews (UoManchester) and Matthias Ehrhardt (UoBath), and funded by EPSRC until 2025 - including support from CoSeC - CCP SyneRBI will provide an Open Source Software platform, enabling faster translation of novel research and technology in image reconstruction of biomedical images from various tomographic imaging systems.
Biomedical imaging is important for medical diagnosis and involves using sophisticated algorithms to reconstruct tissue volumes; it's a routine process from single mode scanners such as: Magnetic Resonance (MR), radionuclide imaging using Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), and X-ray Computed Tomography (CT). Combining data from these sources and analysing them together provides a holistic view of patients' physiology and anatomy, thereby aiding diagnosis. However, combining sources tends to reduce the quality of the images and their analyses, unless incorporating information from multiple scans in methods known as 'synergistic image reconstruction'.
The figure to the left compares images (of carotid arteries) reconstructed with the standard PET reconstruction algorithm, versus a synergistic reconstruction algorithm (using information from both PET and MRI).
Daniel Deidda et al. Inverse Problems 35 (2019) 044001 (24pp)
As their name suggests, CCP PET-MR already made progress in synergistic image reconstruction (of PET and MR images) by building a network of UK and international researchers with considerable expertise in software development and implementation, as well as access to know-how from scanner manufacturers. Reconstructing images from multiple types of scanners is a particularly challenging problem made tractable by exploiting commonly shared patterns and features between the data. Rising to this challenge CCP SyneRBI will continue from CCP PET-MR extending its established network, and concentrating on the logistical and computational aspects of synergistic image reconstruction, including an Open Source Software platform called Synergistic Image Reconstruction Software (SIRF) released via GitHub, in close collaboration with CCPi (CCP on Tomographic Imaging).
For further information see: CCP SyneRBI
