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- Kylberg, Gustaf, et al.
(författare)
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Local Intensity and PCA Based Detection of Virus Particle Candidates in Transmission Electron Microscopy Images
- 2009
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Ingår i: Proc. 6th International Symposium on Image and Signal Processing and Analysis. - Piscataway, NJ : IEEE. - 9789531841351 ; , s. 426-431
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Konferensbidrag (refereegranskat)abstract
- We present a general method using local intensity informationand PCA to detect objects characterized onlyby that they differ from their surroundings. We apply ourmethod to the problem of automatically detecting virus particlecandidates in transmission electron microscopy images.Viruses have very different shapes and sizes, manyspecies are spherical whereas others are highly pleomorphic.To detect any kind of virus particles in electron microscopyimages it is therefore necessary to use a methodnot restricted to detection of a specific shape. The methodproposed here uses only one input parameter, the approximatevirus thickness, which is a conserved feature withina virus species. It is capable to detect virus particles ofvery varying shapes. Results on images with highly texturedbackground of several different virus species are presented.
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| 2. |
- Kylberg, Gustaf, et al.
(författare)
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Segmentation of virus particle candidates in transmission electron microscopy images
- 2012
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Ingår i: Journal of Microscopy. - : Blackwell Publishing. - 0022-2720 .- 1365-2818. ; 245:2, s. 140-147
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we present an automatic segmentation method that detects virus particles of various shapes in transmission electron microscopy images. The method is based on a statistical analysis of local neighbourhoods of all the pixels in the image followed by an object width discrimination and finally, for elongated objects, a border refinement step. It requires only one input parameter, the approximate width of the virus particles searched for. The proposed method is evaluated on a large number of viruses. It successfully segments viruses regardless of shape, from polyhedral to highly pleomorphic.
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| 4. |
- Kylberg, Gustaf, et al.
(författare)
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Virus texture analysis using local binary patterns and radial density profiles
- 2011
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Ingår i: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642250842 ; 7042, s. 573-580
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Konferensbidrag (refereegranskat)abstract
- We investigate the discriminant power of two local and two global texture measures on virus images. The viruses are imaged using negative stain transmission electron microscopy. Local binary patterns and a multi scale extension are compared to radial density profiles in the spatial domain and in the Fourier domain. To assess the discriminant potential of the texture measures a Random Forest classifier is used. Our analysis shows that the multi scale extension performs better than the standard local binary patterns and that radial density profiles in comparison is a rather poor virus texture discriminating measure. Furthermore, we show that the multi scale extension and the profiles in Fourier domain are both good texture measures and that they complement each other well, that is, they seem to detect different texture properties. Combining the two, hence, improves the discrimination between virus textures.
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