Fetal Echocardiography Report

Fetal echocardiography is the name of the test used to diagnose cardiac conditions in the fetal stage. Cardiac defects are amongst the most common birth defects. Their diagnosis is important in the fetal stage as it might provide an opportunity to plan and manage the baby as and when it is born. Specific maternal and fetal conditions suspicious of having cardiac anomalies would indicate the need for this test. The basic view performed in cardiac ultrasound is the four-chamber view, which can detect 43–96% of fetal anomalies. “Extended basic views” of the left ventricular outflow tract (LVOT) and right ventricular outflow tract (RVOT) increase the sensitivity for the detection of anomalies. Alternatively, a comprehensive set of five short axis

2D ultrasound images are made up of a series of thin image 'slices', with only one slice being visible at any one time to create a 'flat' looking picture. Images are presented in 2-D as well as in 3-D domain. In the 2-D domain each element is called pixel, while in 3-D domain it is called voxel. In some cases we represent 3-D images as a sequential series of 2-D slices, this is an advantage associated with 2-D domain representation. Series of fetus images are collected and processed together by 3D ultrasound probe to obtain the 3D images. These images will have the volume (depth) which will be life-like pictures of the fetus. These images will resemble the photos of newborn baby. In 4D Ultrasound, the dimension of time is added, resulting in the movement of the fetus. This newest technology of ultrasound will scan 25 of 3D images continuously per second. 3D ultrasound gives enhanced diagnostic capabilities and can make it easier for less trained people to interpret ultrasound images. In general there are two ways of getting a 3D ultrasound image: By using a 2D array scanner (giving 3D images directly) or by using a series of 2D scans and combine these scans to build a 3D volume. The only practical scanning technique that can be used for portable systems is freehand scanning that combines a series of 2D images. Segmentation accuracy will be better in 2D compared to 3D due to the reduced resolution of matrix

In case of medical image segmentation the aim is to study anatomical structure and identify Region of Interest i.e. locate tumor, lesion and other abnormalities, measure tissue volume to measure growth of tumor. The role of segmentation is crucial in most tasks requiring image analysis. The success or failure of the task is often a direct consequence of the success or failure of segmentation. However, a reliable and accurate segmentation of an image is, in general, very difficult to achieve by purely automatic