Abstract
We present an algorithm to extract a medial representation of proteins in volume images. The representation (MGR) takes into account the internal grey-level distribution of the protein and can be extracted without first segmenting the image into object and background. We show how MGR can facilitate the analysis of the structure of the proteins and thereby also classification. Results are shown on two types of protein images.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Nyström, I., Smedby, Ö.: Skeletonization of volumetric vascular images – distance information utilized for visualization. J. Comb. Opt. 5, 27–41 (2001)
Fouard, C., Malandain, G., Prohaska, S., Westerhoff, M., Cassot, F., Marc-Vergnes, J.P., Mazel, C., Asselot, D.: Skeletonization by blocks for large 3D datasets: Application to brain microcirculation. In: Proc. 2nd. IEEE Int. Symp. Biomed. Imag., pp. 89–92 (2004)
Bitter, I., Kaufman, A.E., Sato, M.: Penalized-distance volumetric skeleton algorithm. IEEE Trans. on Vis. and Comp. Graph. 7, 195–206 (2001)
Svensson, S., Nyström, I., Arcelli, C., Sanniti di Baja, G.: Using grey-level and distance information for medial surface representation of volume images. In: Proc. 16th Int. Conf. on Pat. Rec (ICPR 2002), vol. 2, pp. 324–327. IEEE CS, Los Alamitos (2002)
Sintorn, I.M., Mata, S.: Using grey-level and shape information for decomposing proteins in 3D images. In: Proc. 2nd. IEEE Int. Symp. Biomed. Imag., pp. 800–803 (2004)
De-Alarcón, P.A., Pascual-Montano, A., Gupta, A., Carazo, J.M.: Modeling shape and topology of low-resolution density maps of biological macromolecules. Biophys. J. 83, 619–632 (2002)
Norel, R., Petrey, D., Wolfson, H.J., Nussinov, R.: Examintaiton of shape complementarity in docking of unbound proteins. Prot. Str. Func. Gen. 36, 307–317 (1999)
Liang, J., Edelsbrunner, H., Woodward, C.: Anatomy of protein pockets and cavities: Measurement of binding site geometry and implications for ligand design. Prot. Sci. 7, 1884–1897 (1998)
Edelsbrunner, H.: Biological applications of computational topology. In: Goodman, J.E., O’Rourke, J. (eds.) Handbook of Discrete and Computational Geometry, CRS Press (2004)
Jiménez-Lozano, N., Chagoyen, M., Cuenca-Alba, J., Crazo, J.M.: Femme database: topologic and geometric information of macromolecules. J. Struct. Biol. 144, 104–113 (2003)
Berman, H., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T., Weissig, H., Shindyalova, I., Bourne, P.: The protein data bank. Nucl. Ac. Res. 28, 235–242 (2000)
Pittet, J.J., Henn, C., Engel, A., Heymann, J.B.: Visualizing 3D data obtained from microscopy on the internet. J. Struct. Biol. 125, 123–132 (1999)
Sandin, S., Öfverstedt, L.G., Wikström, A.C., Wrange, O., Skoglund, U.: Structure and flexibility of individual immunoglobulin g molecules in solution. Structure 12, 409–415 (2004)
Skoglund, U., Öfverstedt, L.G., Burnett, R., Bricogne, G.: Maximum-entropy three-dimensional reconstruction with deconvolution of the contrast transfer function: A test application with adenovirus. J. Struct. Biol. 117, 173–188 (1996)
Bertrand, G., Malandain, G.: A new characterization of three-dimensional simple points. Pat. Rec. Let. 15, 169–175 (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sintorn, IM., Gedda, M., Mata, S., Svensson, S. (2005). Medial Grey-Level Based Representation for Proteins in Volume Images. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_52
Download citation
DOI: https://doi.org/10.1007/11492542_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26154-4
Online ISBN: 978-3-540-32238-2
eBook Packages: Computer ScienceComputer Science (R0)