David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP...

15
David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans

Transcript of David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP...

Page 1: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

David AtkinsonJulian Matthews

Claudia PietroAndrew Reader

Kris Thielemans

Page 2: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

Computational Collaborative Projects

• CCPs bring together leading UK expertise in key fields of computational research to tackle large-scale scientific software development, maintenance and distribution.

• The aim is to capitalise on investment by encouraging widespread and long term use of the software, and by fostering new initiatives such as High End Computing consortia.

http://www.ccp.ac.uk/

Page 3: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

CCP in Synergistic PET-MR Reconstruction

• 5 year funding (April 2015 – March 2020)

• Budget for networking activities

• Core support via STFC• Scientific programmers: 1 FTE (for 5 years)• Administration: 0.16 FTE (for 5 years)

• David AtkinsonJulian MatthewsClaudia PietroAndrew ReaderKris Thielemans

Page 4: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

Aims• Network formation: bringing together expertise in each

modality• advancing understanding of PET-MR

• enhancing understanding of the algorithms used for each modality

• Developing software infrastructure• creating an Open Source software platform for integrated PET-MR

image reconstruction

• standardisation of data formats

• database with test cases

Page 5: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

Past Networking Activities Mailing lists and website

Workshops/courses (co-organisers) 2nd International Training School on PET-MRI Engineering, Leeds, 2015

IEEE MIC 2015 Workshop: Open Source Software for Image Reconstruction

IEEE MIC 2015 Short Course: PET/SPECT/CT image reconstruction

IEEE MIC 2015: STIR User's Meeting

BC ISMRM Leeds 2016: half day Educational Workshop on PET-MRI Image reconstruction

UCL PET/MR Symposium 2016

IEEE MIC 2016: STIR User's Meeting

Software Framework Meetings ~6 weekly

10 meetings so far, with average ~15 attendants (local and remote)

Page 6: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

Software• Framework for 3D and 4D reconstruction of PET-MR data

• Simple enough for education and teaching

• Powerful enough for processing of real data in a research context

• Easy installation (e.g. installation script, precompiled, virtual machine, Docker)

• Open Source

Page 7: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

WHY OPEN SOURCE?

• Common platform for research

• Common platform for development

• Interaction with other packages

• Rigorous validation & testing by the community

• Speeds up scientific discoveries & technological evolution

• Great examples with demonstrated impact

GATE

Page 8: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

Architecture overview

POSSUM

Standard file format

for (almost) ‘raw’ data(PET and MR)

PET package 1

PET package 2

MR package 1

MR package 2

Framework

Optimisation Code 1

File format translators supplied by/developed with manufacturers

Images(DICOM,

Nifti,…)

simulators

Page 9: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

Framework

• “Glue” between different packages

•Provides consistent interface to user• It should not matter which package you are using for e.g.

the PET part

• Language interfaces• MATLAB

• Python

Page 10: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

Software Status• Underlying packages:

• Functionality• Basic data manipulation

• Acquisition modelling• PET: geometric, but randoms/scatter/etc in progress

• MR: fully and under-sampled Cartesian

• Access to some reconstruction algorithms• PET: OSEM, OSL, OSSPS

• MR: GRAPPA, SENSE

• Processing of scanner data • Siemens mMR: MR OK, PET OK but not user-friendly

• GE Signa PET/MR: initial code for PET

Page 11: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

Example

image = stir.Image() # STiR image

image.initialise((111, 111, 31), (3, 3, 3.375))

image.fill(1.0)

obj_fun = stir.PoissonLogLh_LinModMean_AcqModData()

grad = obj_fun.gradient(image, 0) # STiR image

i = image.as_array() # Python array (numpy ndarray)

g = grad.as_array() # Python array (numpy ndarray)

f = lambda t: -obj_fun.value(image.fill(i + t*g))

t = scipy.optimize.fminbound(f, 0, tmax)

i = i + t*g

image.fill(i)

Page 12: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

Software distribution

• https://github.com/CCPPETMR• All source code (Apache 2.0 license)

• Installation instructions

• Virtual Machine (VirtualBox)http://www.ccppetmr.ac.uk/downloads• Preinstalled STIR, Gadgetron

• Preinstalled CCP-PETMR software for Python

• Easy update mechanism (choice between stable and experimental)

http://www.ccppetmr.ac.uk

Page 13: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

http://www.ccppetmr.ac.uk/

Mailing lists:Announcements (68), Users (55), Developers (9)

Page 14: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

Exchange programme

Page 15: David Atkinson Julian Matthews Claudia Pietro Andrew Reader Kris Thielemans · 2016. 9. 27. · CCP in Synergistic PET-MR Reconstruction •5 year funding (April 2015 –March 2020)

http://www.ccppetmr.ac.uk/