| 21. |
- Fakhrzadeh, Azadeh, 1981-
(författare)
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Computerized Cell and Tissue Analysis
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The latest advances in digital cameras combined with powerful computer software enable us to store high-quality microscopy images of specimen. Studying hundreds of images manually is very time consuming and has the problem of human subjectivity and inconsistency. Quantitative image analysis is an emerging field and has found its way into analysis of microscopy images for clinical and research purposes. When developing a pipeline, it is important that its components are simple enough to be generalized and have predictive value. This thesis addresses the automation of quantitative analysis of tissue in two different fields: pathology and plant biology.Testicular tissue is a complex structure consisting of seminiferous tubules. The epithelial layer of a seminiferous tubule contains cells that differentiate from primitive germ cells to spermatozoa in a number of steps. These steps are combined in 12 stages in the cycle of the seminiferous epithelium in the mink. The society of toxicological pathology recommends classifying the testicular epithelial into different stages when assessing tissue damage to determine if the dynamics in the spermatogenic cycle have been disturbed. This thesis presents two automated methods for fast and robust segmentation of tubules, and an automated method of staging them. For better accuracy and statistical analysis, we proposed to pool stages into 5 groups. This pooling is suggested based on the morphology of tubules. In the 5 stage case, the overall number of correctly classified tubules is 79.6%.Contextual information on the localization of fluorescence in microscopy images of plant specimen help us to better understand differentiation and maturation of stem cells into tissues. We propose a pipeline for automated segmentation and classification of the cells in a whole cross-section of Arabidopsis hypocotyl, stem, or root. As proof-of-concept that the classification provides a meaningful basis to group cells for fluorescence characterization, we probed tissues with an antibody specific to xylem vessels in the secondary cell wall. Fluorescence intensity in different classes of cells is measured by the pipeline. The measurement results clearly show that the xylem vessels are the dominant cell type that exhibit a fluorescence signal.
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| 22. |
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| 23. |
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| 24. |
- Fakhrzadeh, Azadeh, et al.
(författare)
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Epithelial Cell Segmentation in Histological Images of Testicular Tissue Using Graph-Cut
- 2013
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Ingår i: Image Analysis and Processing – ICIAP 2013. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642411830 - 9783642411847 ; 8157, s. 201-208
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Konferensbidrag (refereegranskat)abstract
- Computerized image processing has provided us with valuable tools for analyzing histology images. However, histology images are complex, and the algorithm which is developed for a data set may not work for a new and unseen data set. The preparation procedure of the tissue before imaging can significantly affect the resulting image. Even for the same staining method, factors like delayed fixation may alter the image quality. In this paper we face the challenging problem of designing a method that works on data sets with strongly varying quality. In environmental research, due to the distance between the site where the wild animals are caught and the laboratory, there is always a delay in fixation. Here we suggest a segmentation method based on the structural information of epithelium cell layer in testicular tissue. The cell nuclei are detected using the fast radial symmetry filter. A graph is constructed on top of the epithelial cells. Graph-cut optimization method is used to cut the links between cells of different tubules. The algorithm is tested on five different groups of animals. Group one is fixed immediately, three groups were left at room temperature for 18, 30 and 42 hours respectively, before fixation. Group five was frozen after 6 hours in room temperature and thawed. The suggested algorithm gives promising results for the whole data set.
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| 25. |
- Fakhrzadeh, Azadeh, et al.
(författare)
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New computerized staging method to analyze mink testicular tissue in environmental research
- 2017
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Ingår i: Environmental Toxicology and Chemistry. - : Wiley. - 0730-7268 .- 1552-8618. ; 36:1, s. 156-164
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Tidskriftsartikel (refereegranskat)abstract
- Histopathology of testicular tissue is considered to be the most sensitive tool to detect adverse effects on male reproduction. When assessing tissue damage, seminiferous epithelium needs to be classified into different stages to detect certain cell damages; but stage identification is a demanding task. The authors present a method to identify the 12 stages in mink testicular tissue. The staging system uses Gata-4 immunohistochemistry to visualize acrosome development and proved to be both intraobserver-reproducible and interobserver-reproducible with a substantial agreement of 83.6% (kappa=0.81) and 70.5% (kappa=0.67), respectively. To further advance and objectify this method, they present a computerized staging system that identifies these 12 stages. This program has an agreement of 52.8% (kappa 0.47) with the consensus staging by 2 investigators. The authors propose a pooling of the stages into 5 groups based on morphology, stage transition, and toxicologically important endpoints. The computerized program then reached a substantial agreement of 76.7% (kappa=0.69). The computerized staging tool uses local ternary patterns to describe the texture of the tubules and a support vector machine classifier to learn which textures correspond to which stages. The results have the potential to modernize the tedious staging process required in toxicological evaluation of testicular tissue, especially if combined with whole-slide imaging and automated tubular segmentation. Environ Toxicol Chem 2017;36:156-164.
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| 26. |
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| 27. |
- Hall, Hardy, et al.
(författare)
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Precision automation of cell type classification and sub-cellular fluorescence quantification from laser scanning confocal images
- 2016
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Ingår i: Frontiers in Plant Science. - : Frontiers Media SA. - 1664-462X. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- While novel whole-plant phenotyping technologies have been successfully implemented into functional genomics and breeding programs, the potential of automated phenotyping with cellular resolution is largely unexploited. Laser scanning confocal microscopy has the potential to close this gap by providing spatially highly resolved images containing anatomic as well as chemical information on a subcellular basis. However, in the absence of automated methods, the assessment of the spatial patterns and abundance of fluorescent markers with subcellular resolution is still largely qualitative and time-consuming. Recent advances in image acquisition and analysis, coupled with improvements in microprocessor performance, have brought such automated methods within reach, so that information from thousands of cells per image for hundreds of images may be derived in an experimentally convenient time-frame. Here, we present a MATLAB-based analytical pipeline to (1) segment radial plant organs into individual cells, (2) classify cells into cell type categories based upon Random Forest classification, (3) divide each cell into sub-regions, and (4) quantify fluorescence intensity to a subcellular degree of precision for a separate fluorescence channel. In this research advance, we demonstrate the precision of this analytical process for the relatively complex tissues of Arabidopsis hypocotyls at various stages of development. High speed and robustness make our approach suitable for phenotyping of large collections of stem-like material and other tissue types.
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| 28. |
- Joffre, Thomas, 1987-, et al.
(författare)
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Characterization of interfacial stress transfer ability in acetylation-treated wood fibre composites using X-ray microtomography
- 2017
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Ingår i: Industrial crops and products (Print). - : Elsevier BV. - 0926-6690 .- 1872-633X. ; 95, s. 43-49
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Tidskriftsartikel (refereegranskat)abstract
- The properties of the fibre/matrix interface contribute to stiffness, strength and fracture behaviour of fibre-reinforced composites. In cellulosic composites, the limited affinity between the hydrophilic fibres and the hydrophobic thermoplastic matrix remains a challenge, and the reinforcing capability of the fibres is hence not fully utilized. A direct characterisation of the stress transfer ability through pull-out tests on single fibres is extremely cumbersome due to the small dimension of the wood fibres. Here a novel approach is proposed: the length distribution of the fibres sticking out of the matrix at the fracture surface is approximated using X-ray microtomography and is used as an estimate of the adhesion between the fibres and the matrix. When a crack grows in the material, the fibres will either break or be pulled-out of the matrix depending on their adhesion to the matrix: good adhesion between the fibres and the matrix should result in more fibre breakage and less pull-out of the fibres than poor adhesion. The effect of acetylation on the adhesion between the wood fibres and the PLA matrix was evaluated at different moisture contents using the proposed method. By using an acetylation treatment of the fibres it was possible to improve the strength of the composite samples soaked in the water by more than 30%.
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| 29. |
- Landström, Anders
(författare)
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Adaptive tensor-based morphological filtering and analysis of 3D profile data
- 2012
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Image analysis methods for processing 3D profile data have been investigated and developed. These methods include; Image reconstruction by prioritized incremental normalized convolution, morphology-based crack detection for steel slabs, and adaptive morphology based on the local structure tensor. The methods have been applied to a number of industrial applications.An issue with 3D profile data captured by laser triangulation is occlusion, which occurs when the line-of-sight between the projected laser light and the camera sensor is obstructed. To overcome this problem, interpolation of missing surface in rock piles has been investigated and a novel interpolation method for filling in missing pixel values iteratively from the edges of the reliable data, using normalized convolution, has been developed.3D profile data of the steel surface has been used to detect longitudinal cracks in casted steel slabs. Segmentation of the data is done using mathematical morphology, and the resulting connected regions are assigned a crack probability estimate based on a statistic logistic regression model. More specifically, the morphological filtering locates trenches in the data, excludes scale regions for further analysis, and finally links crack segments together in order to obtain a segmented region which receives a crack probability based on its depth and length.Also suggested is a novel method for adaptive mathematical morphology intended to improve crack segment linking, i.e. for bridging gaps in the crack signature in order to increase the length of potential crack segments. Standard morphology operations rely on a predefined structuring element which is repeatedly used for each pixel in the image. The outline of a crack, however, can range from a straight line to a zig-zag pattern. A more adaptive method for linking regions with a large enough estimated crack depth would therefore be beneficial. More advanced morphological approaches, such as morphological amoebas and path openings, adapt better to curvature in the image. For our purpose, however, we investigate how the local structure tensor can be used to adaptively assign to each pixel an elliptical structuring element based on the local orientation within the image. The information from the local structure tensor directly defines the shape of the elliptical structuring element, and the resulting morphological filtering successfully enhances crack signatures in the data.
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| 30. |
- Luengo, Cris, et al.
(författare)
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Adaptive structuring elements based on salience information
- 2012
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Ingår i: Lecture Notes in Computer Science. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 0302-9743 .- 1611-3349. ; 7594, s. 321-328, s. 321-328
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Konferensbidrag (refereegranskat)abstract
- Adaptive structuring elements modify their shape and size according to the image content and may outperform fixed structuring elements. Without any restrictions, they suffer from a high computational complexity, which is often higher than linear with respect to the number of pixels in the image. This paper introduces adaptive structuring elements that have predefined shape, but where the size is adjusted to the local image structures. The size of adaptive structuring elements is determined by the salience map that corresponds to the salience of the edges in the image, which can be computed in linear time. We illustrate the difference between the new adaptive structuring elements and morphological amoebas. As an example of its usefulness, we show how the new adaptive morphological operations can isolate the text in historical documents.
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