III. Methodology
The process of fetal abnormality screening normally consists of two
steps: (1) looking for standard planes, (2) evaluation and diagnosis
based on standard planes. When the sonographer sweeping the ultrasound
tube and looking for the standard planes of fetal bodies, it is actually
object detection discussed in computer vision. In order to discriminate
fetal standard planes, a deep neural network based hybrid framework is
proposed. The idea behind the proposed framework is to use an object
detector to locate the Region of Interests (ROI), i.e., fetal head
region, then another network is applied to make further decision on the
extracted ROI. In this work, YOLO-V3(14) is applied as the object
detector, and ResNeXt(15) is employed as the fine-grained classifier.