| 1. |
- Asplund, Teo, et al.
(författare)
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A Faster, Unbiased Path Opening by Upper Skeletonization and Weighted Adjacency Graphs
- 2016
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Ingår i: IEEE Transactions on Image Processing. - 1057-7149 .- 1941-0042. ; 25:12, s. 5589-5600
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Tidskriftsartikel (refereegranskat)abstract
- The path opening is a filter that preserves bright regions in the image in which a path of a certain length L fits. A path is a (not necessarily straight) line defined by a specific adjacency relation. The most efficient implementation known scales as O(min(L, d, Q)N) with the length of the path, L, the maximum possible path length, d, the number of graylevels, Q, and the image size, N. An approximation exists (parsimonious path opening) that has an execution time independent of path length. This is achieved by preselecting paths, and applying 1D openings along these paths. However, the preselected paths can miss important structures, as described by its authors. Here, we propose a different approximation, in which we preselect paths using a grayvalue skeleton. The skeleton follows all ridges in the image, meaning that no important line structures will be missed. An H-minima transform simplifies the image to reduce the number of branches in the skeleton. A graph-based version of the traditional path opening operates only on the pixels in the skeleton, yielding speedups up to one order of magnitude, depending on image size and filter parameters. The edges of the graph are weighted in order to minimize bias. Experiments show that the proposed algorithm scales linearly with image size, and that it is often slightly faster for longer paths than for shorter paths. The algorithm also yields the most accurate results- as compared with a number of path opening variants-when measuring length distributions.
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| 2. |
- Asplund, Teo, et al.
(författare)
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A new approach to mathematical morphology on one dimensional sampled signals
- 2016
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Ingår i: Proceedings of the 23rd International Conference on Pattern Recognition ICPR 2016. - Piscataway, NJ : IEEE Communications Society. - 9781509048472 ; , s. 3904-3909
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Konferensbidrag (refereegranskat)abstract
- We present a new approach to approximate continuous-domain mathematical morphology operators. The approach is applicable to irregularly sampled signals. We define a dilation under this new approach, where samples are duplicated and shifted according to the flat, continuous structuring element. We define the erosion by adjunction, and the opening and closing by composition. These new operators will significantly increase precision in image measurements. Experiments show that these operators indeed approximate continuous-domain operators better than the standard operators on sampled one-dimensional signals, and that they may be applied to signals using structuring elements smaller than the distance between samples. We also show that we can apply the operators to scan lines of a two-dimensional image to filter horizontal and vertical linear structures.
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| 3. |
- Asplund, Teo, et al.
(författare)
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Adaptive Mathematical Morphology on Irregularly Sampled Signals in Two Dimensions
- 2020
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Ingår i: Mathematical Morphology : Theory and Applications. - : Walter de Gruyter. - 2353-3390. ; 4:1, s. 108-126
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes a way of better approximating continuous, two-dimensional morphologyin the discrete domain, by allowing for irregularly sampled input and output signals. We generalizeprevious work to allow for a greater variety of structuring elements, both flat and non-flat. Experimentallywe show improved results over regular, discrete morphology with respect to the approximation ofcontinuous morphology. It is also worth noting that the number of output samples can often be reducedwithout sacrificing the quality of the approximation, since the morphological operators usually generateoutput signals with many plateaus, which, intuitively do not need a large number of samples to be correctlyrepresented. Finally, the paper presents some results showing adaptive morphology on irregularlysampled signals.
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| 4. |
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| 5. |
- Asplund, Teo, et al.
(författare)
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Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes
- 2019
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Ingår i: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing. - Cham : Springer Nature. - 9783030208660 - 9783030208677
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Konferensbidrag (refereegranskat)abstract
- This paper proposes an extension of mathematical morphology on irregularly sampled signals to 3D point clouds. The proposed method is applied to the segmentation of urban scenes to show its applicability to the analysis of point cloud data. Applying the proposed operators has the desirable side-effect of homogenizing signals that are sampled heterogeneously. In experiments we show that the proposed segmentation algorithm yields good results on the Paris-rue-Madame database and is robust in terms of sampling density, i.e. yielding similar labelings for more sparse samplings of the same scene.
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| 6. |
- Asplund, Teo, et al.
(författare)
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Mathematical Morphology on Irregularly Sampled Data in One Dimension
- 2017
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Ingår i: Mathematical Morphology : Theory and Applications. - : Walter de Gruyter. - 2353-3390. ; 2:1, s. 1-24
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Tidskriftsartikel (refereegranskat)abstract
- Mathematical morphology (MM) on grayscale images is commonly performed in the discretedomain on regularly sampled data. However, if the intention is to characterize or quantify continuousdomainobjects, then the discrete-domain morphology is affected by discretization errors that may bealleviated by considering the underlying continuous signal, given a correctly sampled bandlimited image.Additionally, there are a number of applications where MM would be useful and the data is irregularlysampled. A common way to deal with this is to resample the data onto a regular grid. Often this createsproblems where data is interpolated in areas with too few samples. In this paper, an alternative way ofthinking about the morphological operators is presented. This leads to a new type of discrete operatorsthat work on irregularly sampled data. These operators are shown to be morphological operators thatare consistent with the regular, morphological operators under the same conditions, and yield accurateresults under certain conditions where traditional morphology performs poorly
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| 7. |
- Asplund, Teo, et al.
(författare)
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Mathematical Morphology on Irregularly Sampled Signals
- 2017
-
Ingår i: Computer Vision – ACCV 2016 Workshops. - Cham : Springer. - 9783319544267 - 9783319544274 ; , s. 506-520
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Konferensbidrag (refereegranskat)abstract
- This paper introduces a new operator that can be used to ap-proximate continuous-domain mathematical morphology on irregularly sampled surfaces. We define a new way of approximating the continuous domain dilation by duplicating and shifting samples according to a flat continuous structuring element. We show that the proposed algorithm can better approximate continuous dilation, and that dilations may be sampled irregularly to achieve a smaller sampling without greatly com-promising the accuracy of the result.
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| 8. |
- Asplund, Teo
(författare)
-
Precise Image-Based Measurements through Irregular Sampling
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Mathematical morphology is a theory that is applicable broadly in signal processing, but in this thesis we focus mainly on image data. Fundamental concepts of morphology include the structuring element and the four operators: dilation, erosion, closing, and opening. One way of thinking about the role of the structuring element is as a probe, which traverses the signal (e.g. the image) systematically and inspects how well it "fits" in a certain sense that depends on the operator.Although morphology is defined in the discrete as well as in the continuous domain, often only the discrete case is considered in practice. However, commonly digital images are a representation of continuous reality and thus it is of interest to maintain a correspondence between mathematical morphology operating in the discrete and in the continuous domain. Therefore, much of this thesis investigates how to better approximate continuous morphology in the discrete domain. We present a number of issues relating to this goal when applying morphology in the regular, discrete case, and show that allowing for irregularly sampled signals can improve this approximation, since moving to irregularly sampled signals frees us from constraints (namely those imposed by the sampling lattice) that harm the correspondence in the regular case. The thesis develops a framework for applying morphology in the irregular case, using a wide range of structuring elements, including non-flat structuring elements (or structuring functions) and adaptive morphology. This proposed framework is then shown to better approximate continuous morphology than its regular, discrete counterpart.Additionally, the thesis contains work dealing with regularly sampled images using regular, discrete morphology and weighting to improve results. However, these cases can be interpreted as specific instances of irregularly sampled signals, thus naturally connecting them to the overarching theme of irregular sampling, precise measurements, and mathematical morphology.
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| 9. |
- Bernander, Karl B., et al.
(författare)
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Improving the stochastic watershed
- 2013
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Ingår i: Pattern Recognition Letters. - : Elsevier BV. - 0167-8655 .- 1872-7344. ; 34:9, s. 993-1000
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Tidskriftsartikel (refereegranskat)abstract
- The stochastic watershed is an unsupervised segmentation tool recently proposed by Angulo and Jeulin. By repeated application of the seeded watershed with randomly placed markers, a probability density function for object boundaries is created. In a second step, the algorithm then generates a meaningful segmentation of the image using this probability density function. The method performs best when the image contains regions of similar size, since it tends to break up larger regions and merge smaller ones. We propose two simple modifications that greatly improve the properties of the stochastic watershed: (1) add noise to the input image at every iteration, and (2) distribute the markers using a randomly placed grid. The noise strength is a new parameter to be set, but the output of the algorithm is not very sensitive to this value. In return, the output becomes less sensitive to the two parameters of the standard algorithm. The improved algorithm does not break up larger regions, effectively making the algorithm useful for a larger class of segmentation problems.
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| 10. |
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| 11. |
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| 12. |
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| 13. |
- Curic, Vladimir, et al.
(författare)
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Adaptive hit or miss transform
- 2015
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Ingår i: Mathematical Morphology and Its Applications to Signal and Image Processing. - Cham : Springer. - 9783319187198 ; , s. 741-752
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Konferensbidrag (refereegranskat)abstract
- The Hit or Miss Transform is a fundamental morphological operator, and can be used for template matching. In this paper, we present a framework for adaptive Hit or Miss Transform, where structuring elements are adaptive with respect to the input image itself. We illustrate the difference between the new adaptive Hit or Miss Transform and the classical Hit or Miss Transform. As an example of its usefulness, we show how the new adaptive Hit or Miss Transform can detect particles in single molecule imaging.
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| 14. |
- Curic, Vladimir, et al.
(författare)
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Adaptive mathematical morphology – A survey of the field
- 2014
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Ingår i: Pattern Recognition Letters. - : Elsevier BV. - 0167-8655 .- 1872-7344. ; 47, s. 18-28
-
Tidskriftsartikel (refereegranskat)abstract
- We present an up-to-date survey on the topic of adaptive mathematical morphology. A broad review of research performed within the field is provided, as well as an in-depth summary of the theoretical advances within the field. Adaptivity can come in many different ways, based on different attributes, measures, and parameters. Similarities and differences between a few selected methods for adaptive structuring elements are considered, providing perspective on the consequences of different types of adaptivity. We also provide a brief analysis of perspectives and trends within the field, discussing possible directions for future studies.
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| 15. |
- Curic, Vladimir, et al.
(författare)
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Adaptive structuring elements based on salience distance transform
- 2012
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Ingår i: In Proceedings of Swedish Society for Image Analysis, SSBA 2012. - KTH, Stockholm.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Spatially adaptive structuring elements adjust their shape to the local structures in the image, and are often defined by a ball in a geodesic distance or gray-weighted distance metric space. This paper introduces salience adaptive structuring elements as spatially variant structuring elements that modify not only their shape, but also their size according to the salience of the edges in the image. Consequently they have good properties for filtering.
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| 16. |
- Ćurić, Vladimir, 1981-
(författare)
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Distance Functions and Their Use in Adaptive Mathematical Morphology
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- One of the main problems in image analysis is a comparison of different shapes in images. It is often desirable to determine the extent to which one shape differs from another. This is usually a difficult task because shapes vary in size, length, contrast, texture, orientation, etc. Shapes can be described using sets of points, crisp of fuzzy. Hence, distance functions between sets have been used for comparing different shapes.Mathematical morphology is a non-linear theory related to the shape or morphology of features in the image, and morphological operators are defined by the interaction between an image and a small set called a structuring element. Although morphological operators have been extensively used to differentiate shapes by their size, it is not an easy task to differentiate shapes with respect to other features such as contrast or orientation. One approach for differentiation on these type of features is to use data-dependent structuring elements.In this thesis, we investigate the usefulness of various distance functions for: (i) shape registration and recognition; and (ii) construction of adaptive structuring elements and functions.We examine existing distance functions between sets, and propose a new one, called the Complement weighted sum of minimal distances, where the contribution of each point to the distance function is determined by the position of the point within the set. The usefulness of the new distance function is shown for different image registration and shape recognition problems. Furthermore, we extend the new distance function to fuzzy sets and show its applicability to classification of fuzzy objects.We propose two different types of adaptive structuring elements from the salience map of the edge strength: (i) the shape of a structuring element is predefined, and its size is determined from the salience map; (ii) the shape and size of a structuring element are dependent on the salience map. Using this salience map, we also define adaptive structuring functions. We also present the applicability of adaptive mathematical morphology to image regularization. The connection between adaptive mathematical morphology and Lasry-Lions regularization of non-smooth functions provides an elegant tool for image regularization.
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| 17. |
- Curic, Vladimir, et al.
(författare)
-
Salience adaptive structuring elements
- 2012
-
Ingår i: IEEE Journal on Selected Topics in Signal Processing. - 1932-4553 .- 1941-0484. ; 6:7, s. 809-819
-
Tidskriftsartikel (refereegranskat)abstract
- Spatially adaptive structuring elements adjust their shape to the local structures in the image, and are often defined by a ball in a geodesic distance or gray-weighted distance metric space. This paper introduces salience adaptive structuring elements as spatially variant structuring elements that modify not only their shape, but also their size according to the salience of the edges in the image. Morphological operators with salience adaptive structuring elements shift edges with high salience to a less extent than those with low salience. Salience adaptive structuring elements are less flexible than morphological amoebas and their shape is less affected by noise in the image. Consequently, morphological operators using salience adaptive structuring elements have better properties.
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| 18. |
- Curic, Vladimir, et al.
(författare)
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Salience-Based Parabolic Structuring Functions
- 2013
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Ingår i: Mathematical Morphology and Its Applications to Signal and Image Processing. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642382932 ; 7883, s. 183-194
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Konferensbidrag (refereegranskat)abstract
- It has been shown that the use of the salience map based on the salience distance transform can be useful for the construction of spatially adaptive structuring elements. In this paper, we propose salience-based parabolic structuring functions that are defined for a fixed, predefined spatial support, and have low computational complexity. In addition, we discuss how to properly define adjunct morphological operators using the new spatially adaptive structuring functions. It is also possible to obtain flat adaptive structuring elements by thresholding the salience-based parabolic structuring functions.
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| 19. |
- Fakhrzadeh, Azadeh, et al.
(författare)
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Analyzing Tubular Tissue in Histopathological Thin Sections
- 2012
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Ingår i: 2012 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING TECHNIQUES AND APPLICATIONS (DICTA). - : IEEE conference proceedings. ; , s. 1-6
-
Konferensbidrag (refereegranskat)abstract
- We propose a method for automatic segmentation of tubules in the stained thin sections of various tissue types. Tubules consist of one or more layers of cells surrounding a cavity. The segmented tubules can be used to study the morphology of the tissue. Some research has been done to automatically estimate the density of tubules. To the best of our knowledge, no one has been able to, fully automatically, segment the whole tubule. Usually the border between tubules is subtle and appears broken in a straight-forward segmentation. Here we suggest delineating these borders using the geodesic distance transform. We apply this method on images of Periodic Acid Shiffs (PAS) stained thin sections of testicular tissue, delineating 89% of the tubules correctly.
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| 20. |
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| 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
-
Ingår i: Image Analysis and Processing – ICIAP 2013. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642411830 - 9783642411847 ; 8157, s. 201-208
-
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)
-
New computerized staging method to analyze mink testicular tissue in environmental research
- 2017
-
Ingår i: Environmental Toxicology and Chemistry. - : Wiley. - 0730-7268 .- 1552-8618. ; 36:1, s. 156-164
-
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
-
Ingår i: Frontiers in Plant Science. - : Frontiers Media SA. - 1664-462X. ; 7
-
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
-
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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| 31. |
- Luengo, Cris
(författare)
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Constrained and Dimensionality-Independent Path Openings
- 2010
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Ingår i: IEEE Transactions on Image Processing. - 1057-7149 .- 1941-0042. ; 19, s. 1587-1595
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Tidskriftsartikel (refereegranskat)abstract
- Path openings and closings are morphological operations with flexible line segments as structuring elements. These line segments have the ability to adapt to local image structures, and can be used to detect lines that are not perfectly straight. They also are a convenient and efficient alternative to straight line segments as structuring elements when the exact orientation of lines in the image is not known. These path operations are defined by an adjacency relation, which typically allows for lines that are approximately horizontal, vertical or diagonal. However, because this definition allows zig-zag lines, diagonal paths can be much shorter than the corresponding horizontal or vertical paths. This undoubtedly causes problems when attempting to use path operations for length measurements. This paper 1) introduces a dimensionality-independent implementation of the path opening and closing algorithm by Appleton and Talbot, 2) proposes a constraint on the path operations to improve their ability to perform length measurements, and 3) shows how to use path openings and closings in a granulometry to obtain the length distribution of elongated structures directly from a gray-value image, without a need for binarizing the image and identifying individual objects.
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| 32. |
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| 33. |
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| 34. |
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| 35. |
- Luengo, Cris, et al.
(författare)
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Rapid prototyping of image analysis applications
- 2011
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Ingår i: Medical Image Processing: Techniques and Applications. - New York, NY : Springer New York. - 9781441997692 ; , s. 5-25
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 36. |
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| 37. |
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| 38. |
- Luengo Hendriks, Cris L.
(författare)
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Path openings and their applications
- 2010
-
Ingår i: Proceedings SSBA 2010. - Uppsala : Centre for Image Analysis. ; , s. 79-82
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 39. |
- Luengo Hendriks, Cris L., 1974-
(författare)
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Revisiting priority queues for image analysis
- 2010
-
Ingår i: Pattern Recognition. - : Elsevier BV. - 0031-3203 .- 1873-5142. ; 43:9, s. 3003-3012
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Tidskriftsartikel (refereegranskat)abstract
- Many algorithms in image analysis require a priority queue, a data structure that holds pointers to pixels in the image, and which allows efficiently finding the pixel in the queue with the highest priority. However, very few articles describing such image analysis algorithms specify which implementation of the priority queue was used. Many assessments of priority queues can be found in the literature, but mostly in the context of numerical simulation rather than image analysis. Furthermore, due to the ever-changing characteristics of computing hardware, performance evaluated empirically 10 years ago is no longer relevant. In this paper I revisit priority queues as used in image analysis routines, evaluate their performance in a very general setting, and come to a very different conclusion than other authors: implicit heaps are the most efficient priority queues. At the same time. I propose a simple modification of the hierarchical queue (or bucket queue) that is more efficient than the implicit heap for extremely large queues.
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| 40. |
- Malmberg, Filip, et al.
(författare)
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An efficient algorithm for exact evaluation of stochastic watersheds
- 2014
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Ingår i: Pattern Recognition Letters. - : Elsevier BV. - 0167-8655 .- 1872-7344. ; 47, s. 80-84
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Tidskriftsartikel (refereegranskat)abstract
- The stochastic watershed is a method for unsupervised image segmentation proposed by Angulo and Jeulin (2007). The method first computes a probability density function (PDF), assigning to each piece of contour in the image the probability to appear as a segmentation boundary in seeded watershed segmentation with randomly selected seeds. Contours that appear with high probability are assumed to be more important. This PDF is then post-processed to obtain a final segmentation. The main computational hurdle with the stochastic watershed method is the calculation of the PDF. In the original publication by Angulo and Jeulin, the PDF was estimated by Monte Carlo simulation, i.e., repeatedly selecting random markers and performing seeded watershed segmentation. Meyer and Stawiaski (2010) showed that the PDF can be calculated exactly, without performing any Monte Carlo simulations, but do not provide any implementation details. In a naive implementation, the computational cost of their method is too high to make it useful in practice. Here, we extend the work of Meyer and Stawiaski by presenting an efficient (quasi-linear) algorithm for exact computation of the PDF. We demonstrate that in practice, the proposed method is faster than any previously reported method by more than two orders of magnitude. The algorithm is formulated for general undirected graphs, and thus trivially generalizes to images with any number of dimensions.
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| 41. |
- Malmberg, Filip, et al.
(författare)
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Exact evaluation of stochastic watersheds : From trees to general graphs
- 2014
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Ingår i: Discrete Geometry for Computer Imagery. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783319099545 ; 8668, s. 309-319
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Konferensbidrag (refereegranskat)abstract
- The stochastic watershed is a method for identifying salient contours in an image, with applications to image segmentation. The method computes a probability density function (PDF), assigning to each piece of contour in the image the probability to appear as a segmentation boundary in seeded watershed segmentation with randomly selected seedpoints. Contours that appear with high probability are assumed to be more important. This paper concerns an efficient method for computing the stochastic watershed PDF exactly, without performing any actual seeded watershed computations. A method for exact evaluation of stochastic watersheds was proposed by Meyer and Stawiaski (2010). Their method does not operate directly on the image, but on a compact tree representation where each edge in the tree corresponds to a watershed partition of the image elements. The output of the exact evaluation algorithm is thus a PDF defined over the edges of the tree. While the compact tree representation is useful in its own right, it is in many cases desirable to convert the results from this abstract representation back to the image, e. g, for further processing. Here, we present an efficient linear time algorithm for performing this conversion.
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| 42. |
- Malmberg, Filip, 1980-, et al.
(författare)
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Exact Evaluation of Targeted Stochastic Watershed Cuts
- 2017
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Ingår i: Discrete Applied Mathematics. - : Elsevier. - 0166-218X .- 1872-6771. ; 216:2, s. 449-460
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Tidskriftsartikel (refereegranskat)abstract
- Seeded segmentation with minimum spanning forests, also known as segmentation by watershed cuts, is a powerful method for supervised image segmentation. Given that correct segmentation labels are provided for a small set of image elements, called seeds, the watershed cut method completes the labeling for all image elements so that the boundaries between different labels are optimally aligned with salient edges in the image. Here, a randomized version of watershed segmentation, the targeted stochastic watershed, is proposed for performing multi-label targeted image segmentation with stochastic seed input. The input to the algorithm is a set of probability density functions (PDFs), one for each segmentation label, defined over the pixels of the image. For each pixel, we calculate the probability that the pixel is assigned a given segmentation label in seeded watershed segmentation with seeds drawn from the input PDFs. We propose an efficient algorithm (quasi-linear with respect to the number of image elements) for calculating the desired probabilities exactly.
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| 43. |
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| 44. |
- Miettinen, Arttu, et al.
(författare)
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A non-destructive X-ray microtomography approach for measuring fibre length in short-fibre composites
- 2012
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Ingår i: Composites Science And Technology. - : Elsevier BV. - 0266-3538 .- 1879-1050. ; 72:15, s. 1901-1908
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Tidskriftsartikel (refereegranskat)abstract
- An improved method based on X-ray microtomography is developed for estimating fibre length distribution of short-fibre composite materials. In particular, a new method is proposed for correcting the biasing effects caused by the finite sample size as defined by the limited field of view of the tomographic devices. The method is first tested for computer generated fibre data and then applied in analyzing the fibre length distribution in three different types of wood fibre reinforced composite materials. The results were compared with those obtained by an independent method based on manual registration of fibres in images from a light microscope. The method can be applied in quality control and in verifying the effects of processing parameters on the fibre length and on the relevant mechanical properties of short fibre composite materials, e.g. stiffness, strength and fracture toughness.
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| 45. |
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| 46. |
- Pahlberg, Tobias
(författare)
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Wood Fingerprints : Recognition of Sawn Wood Products
- 2014
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis deals with wood fingerprints and presents ways to track sawn wood products through an industrial process using cameras. The possibility to identify individual wood products comes from the biological variation of the trees, where the genetic code, environment and breakdown process creates a unique appearance for every board. This application has much of the same challenges as are found in human biometrics applications.The vision for the future is to be able to utilize existing imaging sensors in the production line to track individual products through a disordered and diverging product flow. The flow speed in wood industries is usually very high and with a high degree of automation. Wood fingerprints combined with automated inspection makes it possible to tailor subsequent processing steps for each product and can bring the operators vital feedback on process parameters.The motivation for this work comes from the wood industry wanting to keep track of products without invasive methods such as bar code stickers or painted labels. In the project Hol-i-Wood Patching Robot, an automatic scanner- and robot system is being developed, where there is a need to keep track of the shuttering panels that are going to be mended by several automatic robot systems. In this thesis, two different strategies to recognize previously scanned sawn wood products are presented. The first approach uses feature detectors to find matching features between two images. This approach proved to be robust even when subjected to moderate geometric- and radiometric image distortions. The recognition accuracy reached 100% when matching high quality scans of Scots pine boards that have more than 20 knots.The second approach uses local knot neighborhood geometry to find point matches between images. The recognition accuracy reached above 99% when matching simulated Scots pine panels with realistically added noise to the knot positions, whilst more than 85% of the knots were found.Both presented approaches proved to be viable options for recognition of sawn wood products. In order to improve the recognition methods further, a larger dataset needs to be acquired and a method to calibrate parameter settings needs to be developed.
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| 47. |
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| 48. |
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| 49. |
- Rübel, Oliver, et al.
(författare)
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Integrating data clustering and visualization for the analysis of 3D gene expression data
- 2010
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Ingår i: IEEE/ACM Transactions on Computational Biology & Bioinformatics. - 1545-5963 .- 1557-9964. ; 7:1, s. 64-79
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Tidskriftsartikel (refereegranskat)abstract
- The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex data sets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss 1) the integration of data clustering and visualization into one framework, 2) the application of data clustering to 3D gene expression data, 3) the evaluation of the number of clusters k in the context of 3D gene expression clustering, and 4) the improvement of overall analysis quality via dedicated postprocessing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.
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| 50. |
- Selig, Bettina, et al.
(författare)
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Automatic measurement of compression wood cell attributes in fluorescence microscopy images
- 2012
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Ingår i: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 246, s. 298-308
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a new automated method for analyzing compression wood fibers in fluorescence microscopy. Abnormal wood known as compression wood is present in almost every softwood tree harvested. Compression wood fibers show a different cell wall morphology and chemistry compared to normal wood fibers, and their mechanical and physical characteristics are considered detrimental for both construction wood and pulp and paper purposes. Currently there is the need for improved methodologies for characterization of lignin distribution in wood cell walls, such as from compression wood fibers, that will allow for a better understanding of fiber mechanical properties. Traditionally, analysis of fluorescence microscopy images of fiber cross-sections has been done manually, which is time consuming and subjective. Here, we present an automatic method, using digital image analysis, that detects and delineates softwood fibers in fluorescence microscopy images, dividing them into cell lumen, normal and highly lignified areas. It also quantifies the different areas, as well as measures cell wall thickness. The method is evaluated by comparing the automatic with a manual delineation. While the boundaries between the various fiber wall regions are detected using the automatic method with precision similar to inter and intra expert variability, the position of the boundary between lumen and the cell wall has a systematic shift that can be corrected. Our method allows for transverse structural characterization of compression wood fibers, which may allow for improved understanding of the micro-mechanical modeling of wood and pulp fibers.
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