https://3demmethods.i2pc.es/index.php?action=history&feed=atom&title=2002Frangakis_Eigenanalysis2002Frangakis Eigenanalysis - Revision history2026-05-24T20:36:37ZRevision history for this page on the wikiMediaWiki 1.44.2https://3demmethods.i2pc.es/index.php?title=2002Frangakis_Eigenanalysis&diff=1879&oldid=prevJjfdez at 13:53, 22 May 20092009-05-22T13:53:53Z<p></p>
<p><b>New page</b></p><div>== Citation ==<br />
Frangakis AS, Hegerl R. Segmentation of two- and three-dimensional data from electron microscopy using eigenvector analysis. J Struct Biol. 2002 138(1-2):105-113.<br />
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== Abstract ==<br />
An automatic image segmentation method is used to improve processing and visualization of data obtained by electron microscopy. Exploiting affinity criteria between pixels, e.g., proximity and gray level similarity, in conjunction with an eigenvector analysis, the image is subdivided into areas which correspond to objects or meaningful regions. Extending a proposal by Shi and Malik (1997, Proceedings of the IEEE conference on Computer Vision and Pattern Recognition, pp. 731-737) the approach was adapted to the field of electron microscopy, especially to three-dimensional application as needed by electron tomography. Theory, implementation, parameter setting, and results obtained with a variety of data are presented and discussed. The method turns out to be a powerful tool for visualization with the potential for further improvement by developing and tuning new affinity.<br />
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== Keywords ==<br />
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== Links ==<br />
Article: http://dx.doi.org/10.1016/S1047-8477(02)00032-1 <br />
== Related software ==<br />
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== Related methods ==<br />
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== Comments ==</div>Jjfdez