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Equalisation of archival microscopic images from immunohistochemically stained tissue sections

Neumann U., Korzyńska A., Lopez C., Lejeune M., Roszkowiak Ł., Bosch R.

Biocybernetics and Biomedical Engineering

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2013

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Vol. 33, no. 1

63--76

EN

A method of image equalisation that reduces non-uniformity of light distribution caused by optical devices and dust on camera sensors is presented. The method explores non-uniformity which occurs in archival images captured by a typical optical set which consists of a light microscope and a digital camera. A sufficient number of images with low density of foreground objects has been used to extract a global map of non-uniformity of the particular microscope and camera. The proposed method consists of two steps: – (1) extraction of the map of non-uniformity based upon a set of chosen images and – (2) correction of images acquired by the optical set. The global map is created based upon a modified value layer, the third layer of HSV colour space. The proposed method has been tested on images of immunohistochemically (IHC) stained samples of a biopsy tissue, and it has been validated using an image segmentation method developed earlier. The results of the light distribution equalization, as well as the equalized images segmentation turn out to be more similar to the reference method results (namely the manual counting results), than the results of the original images segmentation. The equalization method can be used for other types of images, but all of them should be acquired by the same optical set.

2

Multistage morphological segmentation of bright-field and fluorescent microscopy images

Korzyńska A., Iwanowski M.

Opto-Electronics Review

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2012

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Vol. 20, No. 2

174-186

EN

This paper describes the multistage morphological segmentation method (MSMA) for microscopic cell images. The proposed method enables us to study the cell behaviour by using a sequence of two types of microscopic images: bright field images and/or fluorescent images. The proposed method is based on two types of information: the cell texture coming from the bright field images and intensity of light emission, done by fluorescent markers. The method is dedicated to the image sequences segmentation and it is based on mathematical morphology methods supported by other image processing techniques. The method allows for detecting cells in image independently from a degree of their flattening and from presenting structures which produce the texture. It makes use of some synergic information from the fluorescent light emission image as the support information. The MSMA method has been applied to images acquired during the experiments on neural stem cells as well as to artificial images. In order to validate the method, two types of errors have been considered: the error of cell area detection and the error of cell position using artificial images as the "gold standard".

3

A method of estimation of the cell doubling time on basis of the cell culture monitoring data

Korzyńska A., Zychowicz M.

Biocybernetics and Biomedical Engineering

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2008

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Vol. 28, no. 4

75-82

EN

Investigation with time-lapse microscopy of the clonal growth of stem cells provides to the analysis of image sequences, which document development of a single clone in constant time increments. The cell doubling time (T2) determines the dynamics of the cell culture development as average time taken for a cell to complete the cell cycle and is typically estimated with cytometric measurements within several days. However our monitoring of the cell culture lasts shorter, so the dependence of T2 from measurements available from image sequences has been found and applied to the collected data. The results are compared with the cell doubling time estimated and published for the cell line by the lab, in which it has been established.

4

Software for cells images segmentation

Strojny W., Korzyńska A.

Journal of Applied Computer Science

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2003

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Vol. 11, nr 1

91-100

EN

The paper contains the description of software for microscopic cells images segmentation called SeKom. Methods of computer images processing based on texture analysis were used for image sequence recorded cell behaviour, segmentation. The programme is a part of the System of Monitoring of Cells Behaviour elaborated and constructed in Institute of Biocybernetics and Biomedical Engineering, PAS for the project of cell movement and behaviour investigation.