Automatic health monitoring of fetus from ultrasound images using level set algorithm

Ultrasound scan during pregnancy is one of the most important ways to determine the health of the fetus. Ultrasound scanning/imaging helps the obstetrician to get the anatomic measurements of the fetus, thus enabling them to keep track of the health of the fetus. Ultrasound images are low-contrast images with high noise content. Hence it is difficult to obtain the precise anatomic measurements manually and requires more time. In rural areas, where the ratio of number of ultrasound centers to number of patients is very low, it gets increasingly difficult for the health care professionals to invest the required amount of time to get the precise measurements. This paper aims at assisting the obstetrician with an automatically health monitoring of the fetus from the ultrasound images. This is done by first enhancing the image by using a combination of wavelet and Laplacian of Gaussian filter and then finding the anatomic measurements, such as length, perimeter, area etc. by image segmentation using level set algorithm. The experimental result shows the accuracy and effectiveness of the proposed system.