readme This directory contains various algorithms for image reconstruction and other inverse problems such as image restoration and image registration. It also contains code for related applications including MRI pulse design. --- GETTING STARTED After installing the toolbox, use matlab's "path" functionality to put the top level directory in its path (or launch matlab from that directory). Then run the file 'setup.m' and all the subdirectories will be added to the path. You may find it convenient to read setup.m and customize it. I recommend running and examining some of the files in the example/ directory or any of the many ..._example.m files around, such as emission/eml_osem_example.m Many example files prompt you to hit enter before continuing, so you and I can see the output of each stage before proceeding. To change this behaviour, execute 'prompt run' (See utilities/prompt.m for help.) Some of examples may require the binary program "wt" or "op" that are part of Aspire. You can also get Aspire for free by following the instructions on my web pages. There are also a couple of mex files that you may need - wtfmex and f3dmex for example. I distribute these only in linux/mac formats; see mex directory. Part of my motivation for creating these files is to accompany a book on image reconstruction that I am currently writing. If you have any problems with these m-files, or any suggestions whatsover, I welcome your input! --------------------------------------------------------------------------- Jeff Fessler, http://www.eecs.umich.edu/~fessler/ --------------------------------------------------------------------------- --- Subdirectories (in alphabetical order): align: image registration tools blob: SPECT reconstruction with blob basis functions (not recommended) contrib: algorithms contributed by others. these directories are not added to the path by setup.m so the user must modify the path to use them. contrib/ppcd: test routines comparing WLS-CD, WLS-GCD, WLS-PPCD (these are mostly for internal UM use) ct: polyenergetic CT routines (beam hardening, dual energy, etc.) data: data for examples doc: see the pdf file within for some introductory documentation. emission: algorithms for Poisson emission tomography PET/SPECT/ Poisson regression eml_ emission maximum likelihood eql_ emission quadratically penalized likelihood epl_ emission penalized likelihood example: example(s) of usage. there are more examples in other directories too. running any of these examples is a good place to start! fbp: filter-backproject reconstruction, including 2D parallel and fan-beam and 3D Feldkamp (FDK) cone beam reconstruction freemat: work in progress, towards making the code run with freemat general: some algorithms that work for generic image reconstruction problems graph: graphics routines mex: MEX (matlab executables), including some C99 source code mri: MR image reconstruction mri-rf: MR pulse design tools, including Spectral-spatial pulse design for phase precompensatory slice selection. (more to come) nufft: non-uniform FFT toolbox penalty: functions associated with regularization systems: system matrices and system matrix object classes If you are interested in edge-preserving image restoration for a shift-invariant blur model with additive gaussian noise, then start with systems/Gblur_test.m and example/restore_example.m For tomography, consider starting with systems/Gomo2_strip.m, which is used in many of the examples. transmission: algorithms for Poisson transmission tomography tml_ transmission ML tql_ transmission quadratically penalized likelihood tpl_ transmission penalized likelihood utilities: useful matlab utilities for image reconstruction algorithms. wls: algorithms associated with the weighted least squares (WLS) cost function and penalized versions thereof pwls_ penalized weighted least squares qpwls_ quadraticaly penalized weighted least squares Most algorithms also include a test routine... --- Additional notes: Raymod Muzic has matlab routines for reading ECAT files available: www.nuclear.uhrad.com/comkat (I have not yet tried them myself.) There is one known issue with Matlab7. It can store sparse matrices only as doubles with is fine, but if you do "S * x", where S is a sparse matrix and x is a vector of class single, Matlab7 gives an error message rather than politely upgrading x to a double. The object Gsparse.m provides a work around for this. Complain to Matlab loudly that they should fix this annoyance... Windows users: Some of the subdirectories of the "systems" directory contain "links" to m-files in other directories. (These are created using "ln -s" in unix.) These links are also in the .tar file as soft links. But these links may not be recognized by Windoze, resulting in various error messages. They work fine on Mac OSX since that fantastic operating system is unix "under the hood." I recommend that you avoid using Windows. But if you insist, then you will have to figure out how to fix those links or copy the appropriate m-files into the appropriate directories. Another problem is that apparently windoze is case insensitive. I believe I have purged most of the m-files that had capitalized names now. Nevertheless, at this point it would be better to just go buy a Mac...