EXTRACTION OF FETAL FEATURES FROM B MODE ULTRASONOGRAMS FOR EFFICIENT DIAGNOSIS OF DOWN SYNDROME IN FIRST AND SECOND TRIMESTER

Abstract

Segmentation of ultrasound images has been found to be a tedious task due to the presence of speckle and other artifacts. The random nature of the multiplicative speckle noise and lack of demarcation of information in ultrasound images makes the segmentation a highly complex one. In this paper a modified watershed based method has been proposed for segmentation of features from Ultrasound images towards efficient diagnosis of Down Syndrome in first and second trimester. The pixels are grouped based on the pixel differences and the co- occurrence matrix is formed based on the energy and contrast. If global scheme is adopted for segmentation the high frequency edges may appear as artifacts. Hence to overcome this the wavelet transform of co-occurrence matrix is obtained and each decomposed band is subjected to an averaging filter. The process bands are thresholded using Otsu’s method and a binary image is obtained. The isolated pixels are removed by using suitable morphological operations. Then inverse wavelet transform is performed to obtain the image skeleton. The resultant image is subjected to watershed segmentation using gradients. Using the above mentioned approach we can see that the regions of interest are clearly segmented and is producing reproducible results.