An online training course will be provided for the image reconstruction, optimisation and regularisation software packages: Synergistic Image Reconstruction Framework (SIRF) and the Core Imaging Library (CIL). This course will be free (registration required) and of interest to attendees of the Fully3D conference which follows after the course. However, material will start at an introductory level for anyone beginning in the image reconstruction field with interest in software and computing.
The course will cover image reconstruction for PET, MRI and x-ray CT, emphasising commonalities but allowing participants to concentrate on topics that fit their interest.
We plan 3 interactive sessions per week which will be recorded to help participants in different time zones or who have other commitments. In addition, there will be links to recorded lectures, dedicated Slack channels for communication between participants, trainers and developers of SIRF and CIL, and of course open source software (using Python via Jupyter notebooks). This hands-on course will be delivered with pre-configured cloud computing and information for local deployment will be provided (e.g. Docker container).
We will use HackMD to get interaction with the trainees of the training school: https://hackmd.io/@SIRF-CIL-Fully3D/r1AxJKNou
Dates: 28th June – 16th July, 6 core and 3 optional sessions spread over 3 weeks.
Times: times for interactive sessions are 14:00-16:30 BST (= GMT + 01:00).
Logistics
| Date | Event |
|---|---|
| Fri 9th April | Registration opens |
| Tue 8th June | Registration closes |
| Thu 24th June | Release of training material |
Week1: Introduction and basic concepts
| Mon 28th June 14:00 – 16:30 GMT + 01:00 |
14:00 – 15:00 GMT + 01:00 Joint session
15:00 – 16:30 GMT + 01:00 Sequential sessions for different modalities Introduction of software concepts and discussion of relevant notebooks |
| Wed 30th June 14:00 – 16:00 GMT + 01:00 |
(Partially overlapping) sessions for support
|
| Fri 2nd of July 14:00 – 15:30 GMT + 01:00 |
Joint session
|
Week 2: Iterative Reconstruction and Regularisation
| Mon 5th July 14:00 – 16:30 GMT + 01:00 |
14:00 – 15:00 GMT + 01:00 Joint session
15:00 – 16:30 GMT + 01:00 Sequential sessions for different modalities |
| Wed 7th July 14:00 – 16:00 GMT + 01:00 |
(Partially overlapping) sessions for support
|
| Fri 9th of July 14:00 – 15.30 GMT + 01:00 |
Joint session
|
Week 3: Synergistic and Deep Learning
| Mon 12th of July 14:00 – 15:45 GMT + 01:00 |
14:00 – 15:45 GMT + 01:00 Joint session
|
| Wed 14th of July14:00 – 16:30 GMT + 01:00 | (Partially overlapping) sessions for support
|
| Fri 16th of July 14:00 – 16:30 GMT + 01:00 |
Joint session
|
| Fri 16th of July 16:30-17:30 GMT + 01:00 |
Optional social event. |
Organising Committee
Jakob Sauer Jørgensen, DTU , Denmark
Christoph Kolbitsch, PTB, Germany
Edoardo Pasca, UTRI-STFC, UK
Andrew Reader, KCL, UK
Kris Thielemans, UCL, UK (chair)
Software preparation and testing
Evelina Ametova, KIT, Germany
David Atkinson, UCL, UK
Ander Biguri, UCL, UK
Daniel Deidda, NPL, UK
Claire Delplancke, Bath, UK
Gemma Fardell, UKRI – STFC, UK
Ashley Gillman, CSIRO, Australia
Johannes Mayer, PTB, Germany
Laura Murgatroyd, UKRI – STFC, UK
Evgueni Ovtchinnikov, UKRI – STFC, UK
Evangelos Papoutsellis, UKRI – STFC, UK
Georg Schramm, KUL, Belgium
Ryan Warr, Manchester, UK
Administrative and technical support
Alexander Dibbo, UKRI – STFC, UK
Georgia Lomas, UKRI – STFC, UK
Links
CCP SyneRBI – links to SIRF
https://www.ccpsynerbi.ac.uk/
CCPi – links to CIL
https://www.ccpi.ac.uk/cil
Fully3D 2021
https://kuleuvencongres.be/fully3d-2021
HackMD to interact with trainers
https://hackmd.io/@SIRF-CIL-Fully3D/r1AxJKNou
Accessibility Notice
The live training sessions will be held via Zoom where live transcripts are available. Recordings will be available on platforms such as YouTube with subtitles.
The training material is made of jupyter notebooks. Unfortunately currently jupyter does not meet accessibility standards.
Funding
This training is funded by the UK EPSRC grants ‘CCP SyneRBI: Computational Collaborative Project in Synergistic Reconstruction for Biomedical Imaging’ (EP/T026693/1) and ‘Collaborative Computational Project in tomographic imaging’ (CCPi) EP/M022498/1