A Hessian plate filter and shape feature-based approach to automatically localizing the NT VOI of 3D ultrasound data

Abstract The thickness of nuchal translucency (NT) is one of the most important parameters to be detected in prenatal screening during the first trimester of pregnancy. In this paper, an automatic method is proposed for the localization of the volume of interest (VOI) of NT in three-dimensional (3D) ultrasound data. With the size and position of the fetal head and the equation of the sagittal plane in the 3D ultrasound data as the prior knowledge, the method can be divided into three steps. First, a Hessian-based plate filter is proposed to enhance the possible plates in the volume. Second, several VOIs with large filter responses are selected as candidates. Those VOIs consisting of several connected planes are segmented according to the prior knowledge of the sagittal plane. Third, a set of shape features is proposed to select the NT VOI with the maximum probability. Automatic fetal head localization and sagittal plane detection can be achieved using our previously proposed methodology, which means fully automatic NT volume detection could be reached by using our method. The proposed method produces 86.36% localization accuracy with the manual selection as the ground truth.