STFC staff members of the CoSeC team Dr. Edoardo Pasca, Dr. Evgueni Ovtchinnikov, Dr. Gemma Fardell, and Dr. Evangelos
Papoutsellis support the Collaborative Computational Projects (CCPs) for Tomographic imaging (CCPi1) and Synergistic Reconstruction for Biomedical Imaging (CCP SyneRBI2); in November 2019 the two CCPs organised a two day scientific Synergistic Reconstruction Symposium 3. This symposium led to two volumes being published by the Philosophical Transactions of the Royal Society A, edited by Dr. Charalampos Tsoumpas (University of Leeds), Dr. Jakob Sauer Jørgensen (Technical University of Denmark), Dr. Christoph Kolbitsch (Physikalisch-Technische
Bundesanstalt, Germany) and Prof. Kris Thielemans (University College London):
Laura Murgatroyd (graduate scheme, STFC and member of Edoardo's team) and Dr. Papoutsellis provided the visualisation and the data analysis, respectively, featured on the cover page of part 2 (above right) and Daniel Deidda (NPL) provided the figure featured on the cover page of part 1 (above left).
As the preface to these issues states: 'Traditionally, tomographic image reconstruction has focused on estimating images from a single modality and acquisition. This theme issue [part 1] focuses on synergistic image reconstruction, which aims to illustrate more ideas on how to utilise both similarities and complementary information between different data in order to make the synergistic combination of data offer more than the sum of its parts. This research is timely as it accommodates the emergence of multi-modality scanners, big data and intelligent synthesis of information.'
Additionally, 'This second part includes investigations in multispectral X-ray computed tomography, multi-modality imaging systems such as positron emission tomography combined with X-ray computed tomography or magnetic resonance imaging, and diffuse optical tomographic reconstruction encompassing concurrent ultrasound information'.
Dr. Pasca and his team provided substantial contributions in the development of the software that made possible the research highlighted in the following three publications, which illustrates their invaluable support provided via the CoSeC project as highlighted by Dr. Tsoumpas:
- Core Imaging Library (CIL) part I: a versatile Python framework for tomographic imaging;
- Core Imaging Library - Part II: multichannel reconstruction for dynamic and spectral tomography;
- Motion estimation and correction for simultaneous PET/MR (positron emission tomography / magnetic resonance) using the synergistic image reconstruction framework SIRF and CIL.
As the editors describe in the editorial, it is their hope that the open-access software described in these issues points towards a more inclusive and open-access research environment to engage more scientists in state-of-the-art research projects, potentially supported by strong international collaborations.
1CCPi
2CCP SyneRBI
3https://www.ccpsynerbi.ac.uk/symposium2019
