Abstract
Down syndrome is a genetic disorder which occurs due to the presence of an extra chromosome. This trisomy known as trisomy 21 leads to varying degrees of disability from physical disabilities like growth delays to mental disabilities. The paper focuses on exploring the different methodologies for the enhancement of ultrasound images and to extract the feature set from them; using machine learning algorithms to determine the probabilistic measure of the foetus being born with down syndrome. The proposed system aims to develop an end to end application, built upon the previous works in this field, utilising a dataset consisting of ultrasound scans of the first trimester, and hence would provide insights on the prominence of DS in India, and produces the probabilistic measure of the foetus being born with DS, to aid the doctor in prescribing further invasive test.
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Megha, I.M., Vyshnavi Kowshik, S., Ali, S., Malagi, V.P. (2021). A Comprehensive Survey on Down Syndrome Detection in Foetus Using Modern Technologies. In: Satapathy, S., Zhang, YD., Bhateja, V., Majhi, R. (eds) Intelligent Data Engineering and Analytics. Advances in Intelligent Systems and Computing, vol 1177. Springer, Singapore. https://doi.org/10.1007/978-981-15-5679-1_73
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