An automatic body ROI determination for 3D visualization of a fetal ultrasound volume

This paper presents an efficient method to determine a body region-of-interest (ROI) enclosing a fetus in a two-dimensional (2D) key frame that removes some irrelevant matters such as the abdominal area in front of a fetus to visualize a fetal ultrasound volume along with the key frame. In the body ROI determination, a clear frontal view of a fetus lying down floating in amniotic fluid mainly depends on the successful determination of the top bound among the four bounds of an ROI The key idea of our top-bound setting is to locate it in amniotic fluid areas between a fetus and its mother's abdomen, which are dark so as to typically induce local minima of the vertical projection of a key frame. The support vector machines (SVM) classifier, known as an effective tool for classification, tests whether the candidate top bound, located at each of the local minima which are sorted in an increasing order, is valid or not. The test, using textural characterization of neighbor regions around each candidate bound, determines the first valid one as the top bound. The body ROI determination rate as well as resulting 3D images demonstrate that our system could replace a user in allocation of a fetus for its 3D visualization.