[Castor-users] CASToR release 3.0 available

[tmerlin]

Dear CASToR users,

We are pleased to announce that the version 3.0 of CASToR has been 
released.
It is available on the CASToR website: http://www.castor-project.org/

This version provides new features, including:
  - Dynamic model class for kinetic modelling and parametric image 
reconstruction.
  - Deformation class dedicated to image-based transformation for motion 
correction.
  - Image based tool to apply dynamic models on dynamic set of images 
(post-reconstruction kinetic fitting).
  - Update of time-of-flight (TOF) management for PET.
  - Generic iterative algorithm class.

Please find the full changelog in attached.

Hope you enjoy this new version and do not hesitate to send us your 
feedback on the mailing-list.

The CASToR collaboration


-- 
Thibaut MERLIN -- PhD

Docteur en Imagerie Médicale au Laboratoire de Traitement de l'Information Medicale (LaTIM - INSERM UMR 1101)
Institut Brestois de recherche en Bio-Santé (IBRBS)
12 Avenue Foch, 29200 Brest, FRANCE
Tel: 06.75.12.24.90

-------------- next part --------------

## New features
- Add dynamic reconstruction modules which includes:
  - A dynamic model class, dedicated to kinetic modelling / parametric image reconstruction, including several classes:
    - Class for linear model:
      --> several level of application of the models (dynamic frames, respiratory/cardiac gates)
      --> several optimisation methods (nested EM, NNLS, direct (within system matrix) )
      --> interpolation of arterial input curve interpolation on framing protocols
    - Class for Patlak model
      --> automatic Patlak basis function computation from arterial input curve
      --> several optimisation methods (nested EM, NNLS, direct (within system matrix), linear regression )
    - Class for Spectral model from Cunningham et al., Reader et Al.
      --> parameterization of spectral function coefficients (number, rate, etc..)
      --> interpolation of arterial input function on framing protocol
    - Class for 1-tissue compartement model
      --> several optimisation methods (NNLS, LS with ridge-regression)
      --> several integration methods (Weighed parabola overlapping, trapezoid)
    - Template classes, to help implementing new dynamic models
  - A image-based deformation class, dedicated to image-based transformation for motion correction, including the following class:
    - Class for rigid deformation:
      --> transformation performed through vectors containing 3 translation and 3 rotation parameters 
    - Template class, to help implementing new deformation classes
- Image based tool to apply dynamic models on dynamic set of images (post-reconstruction kinetic fitting)
- Gated motion correction management
- Timestamp-based motion correction management (random motion)
- Several additional command-line options
  - Improved selection of framing protocol: Frames start time, duration, gaps from command-line options
  - New command line option to provide gated datasets splitting information
  - Self-included documentation with -help-dynamic, -help-dynamic-model, -help-motion-model options.
- Updated general documentation for dynamic reconstruction, and additionnal documentation for new dynamic classes

- Update of time-of-flight (TOF) management for PET
  - New options for computing TOF weights (accurate vs approximate, precomputed vs computed on the fly), see -proj-common and -help-projm
  - TOF list-mode data file with quantized TOF measurements and the corresponding TOF weights, see general and TOF documentation

- Generic iterative algorithm class
  - vAlgorithm is now the base class for a reconstruction algorithm using 1 or more iterations and possibly subsets
  - iIterativeAlgorithm implements iterative algorithms based on optimization

- RCP-GS
  - probabilistic PET reconstruction, with the possibility of using multimodal data, see -help-prob

## Bug corrections, code changes, that can affect the results in some way
- PET TOF reconstruction is slightly different


## Small bug fixes
- Several but not listed...