This course will be delivered face-to-face at the University of Warwick in our imaging suite.

The majority will focus on practical computational exercises with our computers (no laptop required), with supporting lectures where appropriate.

Some image analysis will be required of which we have Avizo, Dragonfly, VG Studio, ImageJ, MATLAB on-site with sufficient licenses for all attendees.

Course knowledge outcomes:

- Define the lambert beer law and understand importance in reconstruction

- Describe FDK and Iterative reconstruction methods theoretically, and their relative advantages and disadvantages

- Discuss limited data approaches (noisier/fewer projections) with iterative reconstruction

Course skills outcomes:

- Apply both FDK and iterative reconstruction algorithms to real world data independent of system manufacturer

- Implement corrections for centre of rotation, beam hardening and region of interest

- Recognise semi-convergence to stop iterations (iterative reconstruction)

- Formulate faster acquisition strategies reliant on iterative reconstruction

The course will utilise pre-programmed Python scripts exploiting Core Imaging Library, specifically designed to be accessible to those with limited programming knowledge. If you are Python capable, waypoints to adapt code for "exotic" acquistions will be highlighted.

Attendees will require knowledge what projections and CT Data looks like in terms of grey scale, and also some basic use of image analysis software. The course is flexible in what software is used from the following list: Matlab, Avizo, Dragonfly, VG Studio or ImageJ.

This course is suited for:

• CT System Operators who want to step outside of black-box reconstruction provided by the manufacturer, and implement faster acquistion strategies using iterative reconstruction
• CT Experimentalists who want greater control over how their data is reconstructed, and push boundaries of planned experiments knowing algorithm capabilities.

We welcome a mix of both industrial and academic attendees.

Dr Warnett is an Associate Professor in X-ray Imaging at WMG, University of Warwick, with over a decade of experience in exploiting the technique to solve industrial problems from new product development to materials engineering. He has influenced policy in the area with co-authorship of the EPSRC Tomography Roadmap, leading to the recommendation for "higher speed/throughput" CT and a Strategic Equipment EPSRC grant.

Exploiting iterative reconstruction for higher throughput imaging has become a core focus of Dr Warnett's research, but in a repeatable way, evaluating measurement uncertainty and correlating dimensional accuracy with limited data. Jay is a Co-Investigator for the National Research Facility for X-ray Computed Tomography, of which Warwick is the Metrology spoke.

Dr Warnett is an integral part of the imaging community as Secretary to the international conference ToScA and part of the committee for the dimensional XCT conference. He is a part of national and international working groups for developing the new ISO 10360 standard for X-ray Computed Tomography to standardise processes and results. Alongside, Dr Warnett has helped demonstrate the technique to non-engineering groups that have enhanced their applications, such as West Midlands Police and Oxford Natural History Museum.