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Chen, Y.* ; Hrabe, T.* ; Pfeffer, S.* ; Pauly, O. ; Mateus, D. ; Navab, N.* ; Förster, F.*

Detection and identification of macromolecular complexes in cryo-electron tomograms using support vector machines.

In: Proceedings - International Symposium on Biomedical Imaging (9th IEEE International Symposium on Biomedical Imaging (ISBI), 2-5 May 2012, Barcelona). Piscataway, NJ: IEEE, 2012. 1373-1376
Verlagsversion Volltext DOI
Detection and identification of macromolecular complexes in cryo-electron tomograms is challenging due to the extremely low signal-to-noise ratio (SNR). While the state-of-the-art method is template matching with a single template, we propose a 3-step supervised learning approach: (i) pre-detection of candidates, (ii) feature calculation, and (iii) final decision using a support vector machine (SVM). We use two types of features for SVM: (i) correlation coefficients from multiple templates, and (ii) rotation invariant features derived from spherical harmonics. Experiments conducted on both simulated and experimental tomograms show that our approach outperforms the state-of-the-art method.
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Publikationstyp Artikel: Konferenzbeitrag
Schlagwörter Cryo-electron tomography; spherical harmonics; support vector machines; template matching
ISSN (print) / ISBN 1945-7928
e-ISSN 1945-8452
Konferenztitel 9th IEEE International Symposium on Biomedical Imaging (ISBI)
Konferzenzdatum 2-5 May 2012
Konferenzort Barcelona
Konferenzband Proceedings - International Symposium on Biomedical Imaging
Quellenangaben Band: , Heft: , Seiten: 1373-1376 Artikelnummer: , Supplement: ,
Verlag IEEE
Verlagsort Piscataway, NJ