###Adaptive microCT scanning to guide scaffold development in tissue engineering
Project ID: 2228bd1011 (You will need this ID for your application)
Research Theme: Engineering
UCL Lead department: Medical Physics and Biomedical Engineering
Lead Supervisor: Charlotte Hagen
Project Summary:
X-ray microCT has emerged as a key technology in a breadth of sectors which includes biomedicine. Owing to its importance, EPSRC has,in 2020, invested £10 illion to establish the UK’s first user facility for CT and microCT,of which UCL is a direct part. Tissue engineering is an area that can benefit in particular, as the ability to image samples non-destructively and in 3D, allowing to visualise small details in their greater volumetric context, is paramount. This project will develop new microCT scanning approaches, targeted at accommodating the complex imaging needs of tissue engineering, which often requires multi-scale and multi-contrast approaches. The core aims of the project are the development of adaptive scanning schemes by which a sample is scanned successively at higher resolution and/or in a complementary contrast mode (e.g., phase-based contrasts), as well as image-based indicators for guiding those successive scans. The basis for the scans will be a microCT scanner with multi-resolution and multi-scale imaging capabilities, developed within AXIm. The scanner provides attenuation, refraction, and scattering contrasts; the latter is a known proxy for the presence of sub-resolution structures in a sample and can therefore be exploited to “trigger” a high-resolution scan of the area to which the scattering signal is confined. Deep learning based approaches for guiding the adaptive scans will also be explored. It is expected that the research will lead to new scan protocols for tissue engineering scaffolds and that the results will critically feed into the refinement of tissue engineering methodologies. Besides with tissue engineers, the AXIm group collaborates with industry (Nikon X-Tek Systems) and researchers in computational imaging and deep learning (e.g.,Leiden University), and has links with synchrotrons(Diamond, Elettraand the ESRF). The appointed PhD candidate will be exposed to a collaborative scientific environment and be given the opportunity to participate in synchrotron experiments.