- removed
using
statements from the header files - created namespace
sirf
- added default constructor and set_up to MRAcquisitionModel
- implemented sorting of MR images
- Various bug fixes and corrections
BUILD_STIR_WITH_OPENMP
is nowON
by default- Virtual Machine amendments:
- UK English keyboard
- Password protection removed from screen lock
- Gadgetron data processors check for Gadgetron server crash
- More data files in
SIRF/data/examples/MR
- Grayscale plotting enabled
- Created a python
sirf
package (recommended way of importing)- aliased
p(Gadgetron|STIR|Utilities) -> sirf.(Gadgetron|STIR|Utilities)
- added
setup.py
- exposed cmake variable
PYTHON_STRATEGY
. Options:PYTHONPATH
: prefix$PYTHONPATH
(default)SETUP_PY
: execute${PYTHON_EXECUTABLE} setup.py install
CONDA
: do nothing
- aliased
- Added
PYTHON_DEST_DIR
variable, which allows the user to select the install destination of the SIRF python modules.PYTHON_DEST_DIR
is a cached variable which can be updated on the GUI. IfPYTHON_DEST_DIR
is not set, we will install in${CMAKE_INSTALL_PREFIX}/python
. Likewise forMATLAB_DEST_DIR
. - Some improvements to the demos. Note that PET reconstruction demos have somewhat different parameters.
- Implemented PLS Prior
- Implemented 2D Filtered Back Projection
- Access to all MR images and acquisition parameters
- All 8 file IO available (PET: Interfile, MR: HDF5)
- PET
- PETAcquisitionData object creation from scanner name and parameters
- ListmodeToSinograms converter class, also estimating randoms (from delayed coincidences)
- Normalization from ECAT8 (Siemens mMR) and attenuation image
- Build with OpenMP delivers stable and substantially accelerated performance
- More documentation
- Developer's Guide
- Doxygen inline documentation (available on CCP PETMR website)
- More tests (now run via CTest), for Python, Matlab and C++.
- Coverage reporting for Python tests done by ctest
- fixed version number and avoid confusing with wrong tag v0.9.1
- PET data algebra implemented
- Storage scheme (file/memory) management for acquisition data implemented
- Using single precision float Matlab and Python arrays now
- Argument validity checks introduced
- Consistent naming scheme for libraries and modules adopted
- Matlab tests added
- User Guide Appendix on advanced features added
- Storage scheme management
- Programming Gadgetron chains
- Specific versions of dependencies (ISMRMRD, Gadgetron, STIR, SIRF) in SuperBuild
- SuperBuild update for Virtual Machine
- first release