Down syndrome identification and classification using facial features with neural network

The medical image tool named Ultrasound imaging is used for the analysis of fetus behaviour. Due to the presence of noise the quality of these images is low. Proper filtering is required to suppress this noise. Before the fatal development analysis, it is required image processing method. The processed images are then used for the analysis and it helps to take care of the health. Down syndrome is one of the crucial chromosomal disorders. It is due to the presence of a further copy of chromosome 21. The ultrasound imaging helps to point out DS in the earlier stage of pregnancy by handling the image in an efficient manner. In this work, nasal bone identification and texturing methods are used to detect the disease.  Here we designed a nasal bone identification module for the image classification as normal or abnormal. Down syndrome detection utilizes a collection of facial expression images. A compact geometric descriptor is employed for extracting the facial features from the image set. There is no specific treatment for Down syndrome. Thus, early detection and screening of this disability are the best styles for Down syndrome prevention.