Foetal motion classification using optical flow displacement histograms

Foetal movement has been linked with foetal well-being. In the absence of medical input, its estimation depends exclusively on the mother's subjective opinion. Automatic classification of foetal movement from segmented two dimensional ultrasound scans is a step towards automatic estimation of foetal well-being through foetal motion evaluation. In this paper, optical flow displacement histograms are used to train a backpropagation neural network for classifying foetal movement by means of manually segmented frames that were evaluated independently by two medical experts. Results are promising towards developing an automated foetal motion analysis system but there is still the need for further testing of the hypothesis on a larger number of input samples.

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