Extracting fetal heart signals from Doppler using semi-supervised convolutional neural networks
Yuta Hirono,
Chiharu Kai,
Akifumi Yoshida
et al.
Abstract:Cardiotocography (CTG) measurements are critical for assessing fetal wellbeing during monitoring, and accurate assessment requires well-traceable CTG signals. The current FHR calculation algorithm, based on autocorrelation to Doppler ultrasound (DUS) signals, often results in periods of loss owing to its inability to differentiate signals. We hypothesized that classifying DUS signals by type could be a solution and proposed that an artificial intelligence (AI)-based approach could be used for classification. H… Show more
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