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Early diagnosis of threatened premature labor by electrohysterographic recordings – The use of digital signal processing

Lemancewicz A., Borowska M., Kuć P., Jasińska E., Laudański P., Laudański T., Oczeretko E.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 1

302--307

EN

Prevention and early diagnosis of imminent preterm labor are considered to be the most important perinatal challenge nowadays. Significant progress has been observed on postnatal care of premature infants, but without reducing the prevalence of preterm delivery. Our study was focused on comparison of three methods of spectral analysis of electro-hysterographic (EHG) signals: fast Fourier transform (FFT), wavelet transform (WT) and autoregressive modeling (AR). Complexity of the electrohysterographic signals was analyzed by using: the approximate entropy (ApEn), Lempel–Ziv complexity measure (L–Z). Additionally, the work evaluated the applicability of EHG in diagnosing imminent premature labor. EHG signals were recorded among 60 patients with threatened preterm labor symptoms between the 24th and 34th week of pregnancy. Patients included to the study had a shortened cervix (less than 20 mm) without regular uterine contractions recorded on regular cardiotocography (CTG). The women were divided into two groups: those delivering within 7 days – group A (n = 15) and women delivering after 7 days – group B (n = 45). The study confirmed differences in bioelectrical activity of uterus between patients delivering prematurely within 7 days and after from the EHG registration for all analyzed methods.

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Analysis of cell structure in color histological image

Nedzved A., Ablameyko S., Oczeretko E., Półjanowicz W.

Image Processing & Communications

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2005

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Vol. 10, no 1

43-51

EN

One of the basic subjects of studying in histology is the cell structure. The image of a histological cell is characterized by a geometrical complexity and the certain hierarchy of cell structure. In this paper, algorithm for cell structure extraction is proposed. The algorithm consists of two branches. The first is intended for extraction of cells with an unpainted nucleus, another for the painted nucleus. According to cell hierarchical structure, binary images of cells, nucleus, nucleolus and inclusions are created. For computing of topological characteristics, cell is presented as hierarchy of binary images. The first level contains a binary image of cell, the second level contains an image of a nucleus, the third level contains nucleolus and various cellular inclusions.

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Segmentation of color biomedical images

Ablameyko S., Belotserkovsky A., Oczeretko E., Półjanowicz W.

Image Processing & Communications

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2003

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Vol. 9, no 1-2

17-29

EN

The task of color cell image segmentation is considered. Overview of cell image segmentation algorithms is given. A new homogeneity and color characteristics histogram based algorithm of color cell image segmentation is proposed. It includes a modified edge detection algorithm based on Sobel operator and the procedure of RGB-HSV transformation that was applied to decrease number of operations and increase the segmentation quality.