eCTG: an automatic procedure to extract digital cardiotocographic signals from digital images

• Published in: Computer methods and programs in biomedicine 2018-03, Vol.156, p.133-139
• Main Authors: Sbrollini, Agnese, Agostinelli, Angela, Marcantoni, Ilaria, Morettini, Micaela, Burattini, Luca, Di Nardo, Francesco, Fioretti, Sandro, Burattini, Laura
• Format: Article
• Language: English
• Subjects: Cardiotocography; Computerized cardiotocography; Electronic clinical applications; Fetal monitoring; Image processing; Signal processing
• ISSN: 0169-2607; 1872-7565
• DOI: 10.1016/j.cmpb.2017.12.030

•Cardiotocography (CTG) typically provides paper reports.•Digital CTG images are possibly obtained by scanning paper reports.•This paper proposes eCTG procedure to extract digital CTG signals from images.•eCTG was validated by using the CTU-UHB Intrapartum CTG Database by Physionet.•eCTG accurately extracts digital CTG signals from digital CTG images. Cardiotocography (CTG), consisting in the simultaneous recording of fetal heart rate (FHR) and maternal uterine contractions (UC), is a popular clinical test to assess fetal health status. Typically, CTG machines provide paper reports that are visually interpreted by clinicians. Consequently, visual CTG interpretation depends on clinician's experience and has a poor reproducibility. The lack of databases containing digital CTG signals has limited number and importance of retrospective studies finalized to set up procedures for automatic CTG analysis that could contrast visual CTG interpretation subjectivity. In order to help overcoming this problem, this study proposes an electronic procedure, termed eCTG, to extract digital CTG signals from digital CTG images, possibly obtainable by scanning paper CTG reports. eCTG was specifically designed to extract digital CTG signals from digital CTG images. It includes four main steps: pre-processing, Otsu's global thresholding, signal extraction and signal calibration. Its validation was performed by means of the “CTU-UHB Intrapartum Cardiotocography Database” by Physionet, that contains digital signals of 552 CTG recordings. Using MATLAB, each signal was plotted and saved as a digital image that was then submitted to eCTG. Digital CTG signals extracted by eCTG were eventually compared to corresponding signals directly available in the database. Comparison occurred in terms of signal similarity (evaluated by the correlation coefficient ρ, and the mean signal error MSE) and clinical features (including FHR baseline and variability; number, amplitude and duration of tachycardia, bradycardia, acceleration and deceleration episodes; number of early, variable, late and prolonged decelerations; and UC number, amplitude, duration and period). The value of ρ between eCTG and reference signals was 0.85 (P