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Clinical decision support system for early prediction of Down syndrome fetus using sonogram images

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Abstract

In this paper, the segmentation and extraction of features from ultrasound second trimester fetal images have been presented for early detection of Down syndrome. The region of interest and the edges of the segmented region have been obtained using mean shift analysis and Canny operator, respectively. The prime features such as the nasal bone, the palate and the frontal bone have been segmented for estimating the nasal bone length and frontomaxillary facial angle (FMF). It is observed from the results that the rate of growth of nasal bone length is poor and the FMF angle has been found to increase above 85° for fetus with trisomy 21. This analysis may help the physician for better clinical diagnosis.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Muthayammal Engineering College, Rasipuram, 637408, India

    S. Nirmala

  2. Info Institute of Engineering, Kovilpalayam, Coimbatore, 641107, India

    V. Palanisamy

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  1. S. Nirmala
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  2. V. Palanisamy
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Correspondence to S. Nirmala.

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Nirmala, S., Palanisamy, V. Clinical decision support system for early prediction of Down syndrome fetus using sonogram images. SIViP 5, 245–255 (2011). https://doi.org/10.1007/s11760-010-0158-8

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  • DOI: https://doi.org/10.1007/s11760-010-0158-8

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