Technical Info

Lyngby is able to read the following file formats: Analyze, Stimulate, VAPET, and Raw. In addition, if you know how your data is stored within the file, it is quite straightfoward to load your data in by writing a very small conversion file (usually only a couple of lines of code). Instructions and examples are in the manual.

In addition, we have had numerous inquiries regarding DICOM support. Although we can't offer this at the current time, we can direct the user to some excellent format convertors. These can convert your data into the Analyze format, which can then easily be read into Lyngby. We recommend two free convertors at the moment:

• MRIcro, an excellent viewing package available for Microsoft Windows, Linux (x86) and Solaris (x86). See also Chris Rorden's list of converters.
• (X)MedCon, a very comprehensive conversion utility, available for various platforms (including RPM distributions for RedHat Linux).

The Lyngby Toolbox was developed on Linux and SGI platforms, and should run under all platform versions of Matlab v5.2 or higher. However, we encourage users to run under Linux, where we do the majority of our development now.

The Toolbox consists over over 300 files, all of them in Matlab's *.m format. Hence, there is no platform-dependency, and the code is very easy to install. Simply create a directory containing all the Matlab files and add it to your Matlab path - that's it! (See the installation section for step-by-step instructions.)

We also have two overviews of all toolbox function for those that wish to see how the individual Lyngby functions operate together:

• One Lyngby index made with m2html by Guillaume Flandin.
• An other older index made with mat2html.

They comprise of a series of hyperlinked webpages, one for each of Lyngby's over 300 files. Each one contains the help text from the function together with a hyperlinked list of those other functions which it calls, and those which make a call to it. In this way, it is easy to figure out the structure of the Lyngby's code, and is a useful tool for those wishing to add-in their own algorithms. A similar version is accessed from the Matlab (v5 or higher) commandline by typing: >> helpwin('lyngby')

The advantage of using *.m files is several-fold. Firstly, it means Lyngby is very easy to install, even for the most novice Matlab user. Secondly, it means updating Lyngby can by done by simply replacing just those files that have been modified since you installed it (you can see which files have changed via our CVS code-revision control system). Thirdly, as the *.m files are effectively 'source' files, it allows you to see what the Lyngby code is actually doing with the data. This means it is easy for you to add-in your own code, or alter the Lyngby code.

The disadvantage of only using *.m files is purely speed. However, we feel that the advantages outweigh this, especially considering the fact that any user can compile, for their own specific architecture and system, those parts of the code that they feel need some speed improvement.