NEURAL NETWORKS IN PRENATAL DIAGNOSIS OF CLEFT FACIAL SKULL
Quality improving of prenatal diagnosis of facial dysmorphias (FD) is a task, and this task urgency is determined by high incidence of this congenital malformation, as well as high degree of disability in children. Ultrasound is the commonly accepted method for FD diagnosing. Image obtaining in this case is not difficult, in contrast to its interpretation, especially by novice ultrasound diagnostics physicians. The study on effectiveness of artificial neural networks use was made to assess the possibility of work quality improving on FD ultrasound diagnosis in fetus in order to develop ways to improve it. High efficiency has been established by the authors of the base formation technique for artificial neural networks that help in cleft lip and palate diagnosis in fetus based on the U-Net network architecture using a pre-trained ResNet block as an extractor of key features.