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1
Content available remote Biomedical images enhancement based on the properties of morphological spectra
Przytulska M., Kulikowski J. L., Wierzbicka D.
Biocybernetics and Biomedical Engineering
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2015
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Vol. 35, no. 3
206--215
EN
The method enhancing distinctiveness of the micro-morphological structures, developed using the properties of morphological spectra of their monochromatic 2D images, is presented and its effects on the bone section image are statistically compared with enhancements by Sobel, Roberts and Laplace high-pass filters. Comparison of different filters based on statistical parameters of the classes of selected image details is presented. The preferable method for choosing filtering weight coefficients is described and illustrated by an example of processing an electron-microscope image of a biotechnological specimen. The applicability of this approach and possible development directions are discussed.
2
Content available remote Discrimination of Poorly Distinguishable Random Textures by Statistical Analysis of Morphological Spectra
Przytulska M., Kulikowski J. L., Wierzbicka D.
Machine Graphics and Vision
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2011
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Vol. 20, No. 4
455-477
EN
The paper describes a method for discrimination of poorly distinguishable textures based on application of morphological spectra. The textures are analyzed as random fields of specific probability distributions. The samples of textures are thus considered as their instances and so are also their morphological spectra. Some basic properties of morphological spectra, as well as the definition of similarity measure are shortly reminded. The problem of textures discrimination is formulated as similarity assessment of spectral components histograms. For this purpose, various statistics like: mean value, standard deviation, skewness and kurtosis, as well as some secondary statistics based on theformer, are used. A discriminating index is introduced for evaluation of their discriminating properties. The method of evaluating the discriminating power of statistics based on 1st and 2nd level morphological spectra is illustrated by analysis of the spectra of USG liver images in the groups of healthy persons and patients affected by liver fibrosis. A short description of a IASS program used to the calculations is given. The problem of textures discrimination invariant to rotations and parallel translations of images is described. It is shown that the proposed method discriminates statistically the “ill” and “healthy” textures despite the fact that the differences between them are visually not distinguishable.
3
Content available Discrimination of biomedical textures based on logical similarity measure
Kulikowski J. L., Przytulska M., Wierzbicka D.
Journal of Medical Informatics & Technologies
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2011
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Vol. 17
89--95
EN
The paper presents an approach to discrimination of textures in radiological images based on multi-aspect similarity measures composed of logical tests. There are formulated basis assumptions for similarity measures which can be composed by products of partial (single-aspect) similarity measures. On the basis of similarity measures -similarity classes are defined. Next, two types: strong and weak similarity measures are defined. It is shown that they make possible to define similarity measures based on quality objects properties as well as on their numerical parameters. As an example of application of the general concept discrimination of normal and ill (lesions affected) tissues is considered. It is illustrated by analysis of USG images of liver tissues for which morphological spectra and their statistical parameters have been calculated. It is shown that the differences between values of some pairs of corresponding parameters can be used to a construction of an effective algorithm of textures discrimination. This algorithm takes into consideration both, numerical features of the texture samples and some qualitative data concerning the patients. Conclusions are formulated at the end of the paper.
4
Content available remote Visual Retrieval of Documents Based on Their Multi-Aspect Utility Assessment
Kulikowski J, Przytulska M.
Machine Graphics and Vision
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2010
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Vol. 19, No. 3
299-320
EN
Differences between textual and visual documents retrieval problems are described. It is shown that retrieval of visual documents in experimental data bases requires assessment of image utility and taking it into consideration. A definition of multi-aspect image usefulness measure is proposed. A multi-aspect measure of similarity of images based on their quantitative and/or qualitative features is also proposed. The general concept is illustrated by examples of using morphological spectra as a source of parameters useful in the assessing similarity of some classes of biomedical images. The basic structure and properties of an Image Analysis and Selection System (IASS) are presented as an example of practical realization of the visual documents retrieval methods.
5
Content available remote Description of biomedical textures by statistical properties of morphological spectra
Kulikowski J. L., Przytulska M., Wierzbicka D.
Biocybernetics and Biomedical Engineering
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2010
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Vol. 30, no. 3
19-34
EN
A class of mathematical model s of biological textures based on the multi-variable probability distributions of their morphological spectra is described. It is shown that a large class of such distributions can be presented by sufficient statistics consisting of the coefficients of their expansion into the series of multi-variable Hermite polynomials. The sufficient statistics can then be simplified by rejection of higher-order terms. The general concepts of mathematical models construction are illustrated by examples of textures of several biological tissues (aorta walls, liver and blood). The role of statistics based on absolute values of morphological spectral components and of their cross-correlation coefficients is underlined.
6
Content available remote Comparison of SPECT cerebral images examination methods based on luminance level and morphological spectra evaluation
Przytulska M., Kulikowski J. L., Bajer A., Królicki L.
Biocybernetics and Biomedical Engineering
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2009
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Vol. 29, no. 1
29-42
EN
It is presented a method of SPECT (single-photon emission tomography) cerebral images examination based on morphological spectra. The advantages of the SPECT imaging in early diagnosing of encephalic diseases are emphasized. The detected radiation levels in the SPECT imaging are visualized by luminance levels which give insight into the lesions of cerebral tissue. It is shown that a rough, on luminance level based, examination of the SPECT images can be improved if more sophisticated analytical methods are used. Basic notions and properties of morphological spectra and their applicability as tools for biomedical image analysis are shortly reminded. A simple formula for reversing transformation reconstructing of original image on the basis of a given morphological spectrum is presented. Results of experiments consisting in comparison of the morphological spectra calculated for selected pairs of testing windows in the SPECT cerebral images are shown. It has been shown that the morphological spectra can better suit to an effective comparison of views of the cerebral regions located symmetrically with respect to the brain axis separating the left and right cerebral hemispheres than the averaged luminance level.
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