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Proceedings Paper

Recognition of viruses by electron microscopy using higher order spectral features
Author(s): C.L. Hannah Ong; Vinod Chandran
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Paper Abstract

A limitation of using electron microscopy as a diagnostic tool in virology is the expertise required in analysing and interpreting the images. EM images of different viruses can be very similar in shape. An automated recognition method is proposed in this paper. It is based on radial spectra of higher-order spectral parameters robust to translation, scaling and noise. These features are also roation invariant and can be averaged for a population of viral particles without the need to normalize and align them. They extract symmetry information and are sensitive enough to distinguish viruses that appear nearly circular to the human eye. The method was tested using three such viruses with very similar morphologies - the Adeno, the HAV and the Astro. 70 viral particles of each class from three images were used for training. In the first test, random unseen sets of viral particles form the same images were chosen. In the second test, images of viruses from other sources, where the specimen preparation and the microscope are different, were used to determine the reliability of the system. Both tests have shown high classification accuracy improving rapidly to 100% as the test ensemble grew to 20 particles.

Paper Details

Date Published: 15 May 2003
PDF: 9 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.480646
Show Author Affiliations
C.L. Hannah Ong, Queensland Univ. of Technology (Australia)
Vinod Chandran, Queensland Univ. of Technology (Australia)


Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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