A Probabilistic Template Model for Finding Macromolecules in MET Volume Images

Abstract

We introduce and investigate probabilistic templates with particular focus on the application of protein identification in electron tomography volumes. We suggest to create templates with a weighted averaging operation of several object instances after alignment of an identified subpart. The subpart to be aligned should, ideally, correspond to a rigid and easily identifiable part of the object. The proposed templates enables common rigid template matching methods to also find different shape variations without increasing time complexity in the actual search procedure, since a static template is still used. We present general ideas on how to perform the object instance alignment and look specifically at how to do it for the antibody macromolecule IgG.

Published in

Lecture Notes in Computer Science
2013, volume: 7887, pages: 855-862
Title: Pattern Recognition and Image Analysis : 6th Iberian Conference, IbPRIA 2013, Funchal, Madeira, Portugal, June 5-7, 2013. Proceedings
Publisher: Springer Verlag

Conference

6th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA), JUN 05-07, 2013, Madeira, PORTUGAL

SLU Authors

• Svensson, Lennart

  • Centre for Image Analysis, Swedish University of Agricultural Sciences
    

• Sintorn, Ida-Maria

  • Centre for Image Analysis, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Computer Science

Publication identifier

• DOI: https://doi.org/10.1007/978-3-642-38628-2_101
• ISBN: 978-3-642-38627-5
• eISBN: 978-3-642-38628-2

Permanent link to this page (URI)

https://res.slu.se/id/publ/53258