X-Git-Url: http://git.kpe.io/?p=ctsim.git;a=blobdiff_plain;f=NEWS;h=2da1deef76d3f455010eff6694059d53c2a83538;hp=1938d04f8627d04be6eccc28e811c98107f8b0b3;hb=130313545159177ab450ddd249a49096cfdb1376;hpb=98f894fe74f1a532f5e6d69cca0404d9a58893e7 diff --git a/NEWS b/NEWS index 1938d04..2da1dee 100644 --- a/NEWS +++ b/NEWS @@ -1,17 +1,59 @@ -Version 2.0 of CTSim has been released! +Version 3.0 New Features + +* Greatly improved dialog boxes + +* Online and print manuals with context-sensitive help! + +* 3-d rotating views of image files + +* Creation of arbitrary filter images + +* Cubic interpolation for reconstructions + +* All features of command line tools are now in graphical ctsim program! + +* Complex-valued image files now supported, lots of image math + functions added including Fourier transformations + +* Visual and statistical image comparision functions + +* Plotting of row and column data of single and comparison images + +* Histogram Plotting + +* Conversion of projections to polar images + +* Improved animation graphics + +* New Microsoft Windows compatible self-installer with explorer extensions +to CTSim files + + + +Version 2.5 of CTSim has been released! + +New Features of CTSim version 2.5: + +- Now compiles with Microsoft Visual C++. + +- First Microsoft Windows graphical user interface + +- Bug fixes and modest documentation and program improvements over version 2.0 + New Features of CTSim version 2.0: - Entire code-base cleaned up, re-written, and converted from C to C++. +- Graphical user interface now included! Animation of projection and + reconstruction processes. Displays projection and image files. Uses + platform-independent wxWindows library so can run on UNIX and + Microsoft Windows platforms. + - Integrated G2 library for graphical display from command line tools (UNIX only) -- Graphic front-end (ctsim) initial implemention. Can display - projection and image files. Uses platform-independent wxWindows - so can run on UNIX and Windows platforms. - - Added frequency-based filtering. Can provide significant speed-up in reconstructions compared to convolution-based filtering.