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    A Simple and Effective Approach for Digitization of the CTG Signals from CTG Traces
    (Elsevier Science Inc, 2019) Comert, Z.; Sengur, A.; Akbulut, Y.; Budak, U.; Kocamaz, A. F.; Gungor, S.
    Objectives: Cardiotocography (CTG) is a useful tool for monitoring of the fetal heart rate (FHR) and uterine contractions (UC) during the intrauterine life. Generally, CTG is provided on a printed paper which is hard to save for future evaluations. So, digitization of CTG signals is in demand for future evaluations. A straightforward approach for digitization of the CTG signals is to apply image processing on the scanned CTG printed papers. Material and methods: In this paper, an automatic procedure is proposed for digitization of the CTG signals. The proposed approach consists of four main stages such as pre-processing, image segmentation, signal extraction and signal calibration. The pre-processing stage covers median filtering and contrasts limited adaptive histogram equalization (CLAHE) for noise removal and contrast enhancement. Image segmentation is used to binarize the CTG images for signal determination using the Otsu's thresholding algorithm. The signal extraction is carried out by a two-stepped algorithm. The acquired CTG signals are then calibrated for obtaining the final CTG signals. We use the correlation coefficient to measure the similarity between the automatically digitized CTG signals and original signals. Results: In experimental works, an open-access database, which contains 552 CTG recordings, is employed. The results are quite impressive. According to the obtained results, the average correlation coefficients for FHR and UC signals are 0.9715 +/- 0.0168 and 0.9717 +/- 0.0465, respectively. Conclusions: The obtained results show that the proposed method is quite efficient in digitization of the CTG signals. In future works, this tool will be used to digitize the recordings belonging to the antepartum period collected from the obstetrics clinics in Medical Park Hospital in Elazig, Turkey. (C) 2019 AGBM. Published by Elsevier Masson SAS. All rights reserved.