Training School for the Synergistic Image Reconstruction Framework (SIRF) and Core Imaging Library (CIL)

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Training School for the Synergistic Image Reconstruction Framework (SIRF) and Core Imaging Library (CIL)

 

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

  1. Introduction to the course
  2. Overview of topics for the week
  3. Demonstration on tools used for the course

15:00 – 16:30 GMT + 01:00 Sequential sessions for different modalities

Introduction of software concepts and discussion of relevant notebooks

  1. 15:00-15:30 GMT + 01:00 MR
  2. 15:30-16:00 GMT + 01:00 PET
  3. 16:00-16:30 GMT + 01:00 CT
Wed 30th June
14:00 – 16:00 GMT + 01:00
(Partially overlapping) sessions for support

  1. 14:00 – 15:00 GMT + 01:00 PET
  2. 14:30 – 15:30 GMT + 01:00 MR
  3. 15:00 – 16:00 GMT + 01:00 CT
Fri 2nd of July
14:00 – 15:30 GMT + 01:00
Joint session

  1. Summary of main learning objectives
  2. Example solutions
  3. Overview of next week

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

  1. Introduction to iterative reconstruction and regularisation
  2. Implementation in SIRF/CIL

15:00 – 16:30 GMT + 01:00 Sequential sessions for different modalities

  1. 15:00-15:30 GMT + 01:00 CT
  2. 15:30-16:00 GMT + 01:00 MR
  3. 16:00-16:30 GMT + 01:00 PET
Wed 7th July
14:00 – 16:00 GMT + 01:00
(Partially overlapping) sessions for support

  1. 14:00 – 15:00 GMT + 01:00 PET
  2. 14:30 – 15:30 GMT + 01:00 MR
  3. 15:00 – 16:00 GMT + 01:00 CT
Fri 9th of July
14:00 – 15.30 GMT + 01:00
Joint session

  1. Summary of main learning objectives
  2. Example solutions
  3. Overview of next week

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

  1. Introduction to the week
  2. Synergistic reconstruction
  3. Post-reconstruction Deep Learning
Wed 14th of July14:00 – 16:30 GMT + 01:00 (Partially overlapping) sessions for support

  1. 14:00 – 15:30 GMT + 01:00 Synergistic Reconstruction
  2. 15:00 – 16:30 GMT + 01:00 Deep Learning
Fri 16th of July
14:00 – 16:30 GMT + 01:00
Joint session

  1. Summary of main learning objectives
  2. Example solutions
  3. Wrap up
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

June 28, 2021

9:00 am

16/07/2022