[Insight-users] Introducing MATITK - a MATLAB library allowing ITK algorithms to be called in MATLAB

[Vincent Chu]

We are pleased to introduce MATITK - a MATLAB library (mex file) allowing
numerous ITK algorithms to be called in MATLAB.

Background: ITK is a powerful open-source toolkit implementing
state-of-the-art algorithms in medical image processing and analysis.
MATLAB, on the other hand, is well-known for its easy-to-use, powerful
prototyping capabilities that significantly improve productivity. With the
help of MATITK, biomedical image computing researchers familiar with
MATLAB can harness the power of ITK algorithms while avoiding learning C++
and dealing with low-level programming issues.

More details about MATITK have been presented at:

V. Chu, G. Hamarneh, "MATITK: MATLAB-ITK Interface for Medical Image
Processing", 1st Annual Medical Technology Research Showcase, Vancouver,
BC, 2005.

http://www.cs.sfu.ca/~hamarneh/ecopy/medical_showcase2005a.pdf

More details will be presented in

V. Chu, G. Hamarneh, "MATLAB-ITK Interface for Medical Image Filtering,
Segmentation, and Registration", Proceedings of SPIE Medical Imaging.
(accepted).

http://www.cs.sfu.ca/~hamarneh/ecopy/spiemi2006a.pdf

The latest version of MATITK supporting ITK2.4 has been recently submitted
to the Insight Journal (2005 August - December) which is now open for
review.

http://www.insight-journal.org/view_reviews.php?back=publications.php%3Fjournalid%3D3%26order%3D%26revision_display%3D&pubid=66

Installing and using MATITK is extremely simple (see examples below).
Visit http://www.cs.sfu.ca/~hamarneh/software/matitk/ for an introduction,
complete the form on http://www.cs.sfu.ca/~hamarneh/request_passwd.html to
obtain the password for downloading. Note: MATITK is available for MS
Windows only at this time.

Please report any comments/bugs to: Vincent Chu <vwchu at sfu.ca>, Ghassan
Hamarneh <hamarneh at cs.sfu.ca> (this message also appears when the user
types matitk('?'); or matitk).

Example MATITK commands in MATLAB:
==================================
%mri is a sample volumetric MR brain data set that comes with matlab
load mri;
D=squeeze(D); %singleton dimension removed to obtain 3D array


%List version and support information
matitk('?');
%List out what filtering algorithms are available
matitk('F';
%List out what parameters are needed to perform
CurvatureAnisotropicDiffusionImageFilter
matitk('FCA');

%Perform CurvatureAnisotropicDiffusionImageFilter on image D with the
number of iterations, timestep, and conductance being 5, 0.0625 and 3
respectively.
b=matitk('FCA',[5 0.0625 3],double(D));

%Perform ConfidenceConnectedImageFilter on image b with multipler, number
of iteration and replacement value being 1.4, 10, and 255 respectively.
c=matitk('SCC',[1.4 10 255],double(b),[],[102 82 25]);

subplot(131);imagesc(squeeze(D(:,:,15)));axis image;colormap gray
subplot(132);imagesc(squeeze(b(:,:,15)));axis image;colormap gray
subplot(133);imagesc(squeeze(c(:,:,15)));axis image;colormap gray



Enjoy!

Best Regards,

MATITK Team:
Vincent Chu 		http://www.vincentchu.com		(software implementation)
Ghassan Hamarneh  	http://www.MedicalImageAnalysis.com 	(project idea and supervision)