An effective digitization method for CTG paper report with binary background grids taken by smartphone. (March 2021)

• Record Type: Journal Article
• Authors: Zhao, Zhidong; Liu, Zhikang; Si, Yingsong; Zhang, Yu; Ye, Haihui
• Is Part Of: Computer methods and programs in biomedicine. Volume 200(2021)
• Publication Date: 2021-03
• Subjects: CTG signal digitization -- Binary background grid removal -- Extraction of CTG signal -- Image geometric distortion; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2020.105872
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Overcome the drawback that the existing digitization methods cannot extract CTG signal completely from paper reports with binary background grids. Through a projection map to synchronize the signal, the distortion effect of the mobile phone is removed, which is neglected by the existing digitization methods. Compared with clinical signals, no significant difference is found in the feature of digitization CTG. The digitization signal can be used in clinical diagnosis, according to the judgement of experienced doctors. Abstract: Background and Objective: Cardiotocography (CTG) is the most popular prenatal diagnostic examination, which includes continuous monitoring of foetal heart rate (FHR, bpm) and uterine contraction (UC, mmHg) signals. Compared with CTG paper reports, digitized reports have better storage, transmission and retrieval capabilities, in addition to being able to assess foetal health. However, most of the existing digitization methods extract signals from paper reports with colour background grids, and they cannot extract signals completely from paper reports with binary background grids, which are widely used in clinical CTG monitoring. Moreover, the existing digitization algorithms often neglect the image distortion caused by the imaging equipment. Methods: To overcome the above drawbacks, a digitization method for CTG paper reports with binary background grids taken by smartphones is proposed in this paper. In the stage of removing the grid background, a region merger based on super-pixels and an improved binary line mask removal are designed. Then, signal extraction is performed separately according to the different states of the image column. Through a projection map used to synchronize the signal, the distortion effect of the mobile phone is removed. Results: The experimental results show that the average correlation coefficient (ρ) between the recovery signal obtained by the proposed method and the reference signal is 0.9855±0.0108 for FHR and 0.9866 ± 0.1020 for UC, and the root mean square errors (RMSE) of FHR and UC processed by the proposed method are 1.0366 ± 0.4953 and 2.0355 ± 1.0246, and the mean absolute errors (MAE) of FHR and UC processed by the proposed method are 0.8735 ± 0.0684 and 1.4991 ± 0.2837, which are higher than those of the existing digitization methods. Compared with clinical signals, no significant difference is found in the feature of digitization CTG. Conclusion: The proposed digitization method is a promising useful tool to realize the electronization of CTG signal.