## 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...