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- Hauser, Janosch, et al.
(författare)
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A microfluidic device for TEM sample preparation
- 2020
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Ingår i: Lab on a Chip. - : Royal Society of Chemistry. - 1473-0197 .- 1473-0189. ; 20:22, s. 4186-4193
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Tidskriftsartikel (refereegranskat)abstract
- Transmission electron microscopy (TEM) allows for visualizing and analyzing viral particles and has become a vital tool for the development of vaccines and biopharmaceuticals. However, appropriate TEM sample preparation is typically done manually which introduces operator-based dependencies and can lead to unreliable results. Here, we present a capillary-driven microfluidic single-use device that prepares a TEM grid with minimal and non-critical user interaction. The user only initiates the sample preparation process, waits for about one minute and then collects the TEM grid, ready for imaging. Using Adeno-associated virus (AAV) particles as the sample and NanoVan (R) as the stain, we demonstrate microfluidic consistency and show that the sample preparation quality is sufficient for automated image analysis. We further demonstrate the versatility of the microfluidic device by preparing two protein complexes for TEM investigations using two different stain types. The presented TEM sample preparation concept could alleviate the problems associated with human inconsistency in manual preparation protocols and allow for non-specialists to prepare TEM samples.
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| 4. |
- Kylberg, Gustaf, 1983-
(författare)
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Automatic Virus Identification using TEM : Image Segmentation and Texture Analysis
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Viruses and their morphology have been detected and studied with electron microscopy (EM) since the end of the 1930s. The technique has been vital for the discovery of new viruses and in establishing the virus taxonomy. Today, electron microscopy is an important technique in clinical diagnostics. It both serves as a routine diagnostic technique as well as an essential tool for detecting infectious agents in new and unusual disease outbreaks.The technique does not depend on virus specific targets and can therefore detect any virus present in the sample. New or reemerging viruses can be detected in EM images while being unrecognizable by molecular methods.One problem with diagnostic EM is its high dependency on experts performing the analysis. Another problematic circumstance is that the EM facilities capable of handling the most dangerous pathogens are few, and decreasing in number.This thesis addresses these shortcomings with diagnostic EM by proposing image analysis methods mimicking the actions of an expert operating the microscope. The methods cover strategies for automatic image acquisition, segmentation of possible virus particles, as well as methods for extracting characteristic properties from the particles enabling virus identification.One discriminative property of viruses is their surface morphology or texture in the EM images. Describing texture in digital images is an important part of this thesis. Viruses show up in an arbitrary orientation in the TEM images, making rotation invariant texture description important. Rotation invariance and noise robustness are evaluated for several texture descriptors in the thesis. Three new texture datasets are introduced to facilitate these evaluations. Invariant features and generalization performance in texture recognition are also addressed in a more general context.The work presented in this thesis has been part of the project Panvirshield, aiming for an automatic diagnostic system for viral pathogens using EM. The work is also part of the miniTEM project where a new desktop low-voltage electron microscope is developed with the aspiration to become an easy to use system reaching high levels of automation for clinical tissue sections, viruses and other nano-sized particles.
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| 6. |
- Kylberg, Gustaf, et al.
(författare)
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Detecting Virus-like Particles Using Transmission Electron Microscopy
- 2009
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Ingår i: Proceedings SSBA 2009, Symposium on Image Analysis. - Halmstad : EIS, Halmstad University. - 9789163339240 ; , s. 13-16
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We present a multi scale approach for automating the image acquisition process for an computerized virus diagnostic application. Our methods are designed to mimic the methodology used by virus TEM experts manually operating the microscope. The methods decrease the search area considerably. In addition we present a segmentation method for virus-like particles based on local intensity information and PCA. This method makes no assumption regarding shape which is vital since many viruses are highly pleomorphic, i.e., have different shapes. The only input parameter used is the approximate virus thickness, which is a conserved feature within a virus species.
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| 7. |
- Kylberg, Gustaf, et al.
(författare)
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Evaluation of noise robustness for local binary pattern descriptors in texture classification
- 2013
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Ingår i: EURASIP Journal on Image and Video Processing. - : Springer. - 1687-5176 .- 1687-5281. ; :17
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Tidskriftsartikel (refereegranskat)abstract
- Local binary pattern (LBP) operators have become commonly used texture descriptors in recent years. Several new LBP-based descriptors have been proposed, of which some aim at improving robustness to noise. To do this, the thresholding and encoding schemes used in the descriptors are modified. In this article, the robustness to noise for the eight following LBP-based descriptors are evaluated; improved LBP, median binary patterns (MBP), local ternary patterns (LTP), improved LTP (ILTP), local quinary patterns, robust LBP, and fuzzy LBP (FLBP). To put their performance into perspective they are compared to three well-known reference descriptors; the classic LBP, Gabor filter banks (GF), and standard descriptors derived from gray-level co-occurrence matrices. In addition, a roughly five times faster implementation of the FLBP descriptor is presented, and a new descriptor which we call shift LBP is introduced as an even faster approximation to the FLBP. The texture descriptors are compared and evaluated on six texture datasets; Brodatz, KTH-TIPS2b, Kylberg, Mondial Marmi, UIUC, and a Virus texture dataset. After optimizing all parameters for each dataset the descriptors are evaluated under increasing levels of additive Gaussian white noise. The discriminating power of the texture descriptors is assessed using tenfolded cross-validation of a nearest neighbor classifier. The results show that several of the descriptors perform well at low levels of noise while they all suffer, to different degrees, from higher levels of introduced noise. In our tests, ILTP and FLBP show an overall good performance on several datasets. The GF are often very noise robust compared to the LBP-family under moderate to high levels of noise but not necessarily the best descriptor under low levels of added noise. In our tests, MBP is neither a good texture descriptor nor stable to noise.
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| 10. |
- 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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