Ultrasound Marker Assessment for Nuchal Translucency

Prenatal diagnosis of fetal abnormities including measurement of Nuchal Translucency (NT) using ultra-sonography is widely practiced during early pregnancy. The drawback of current NT measurement technique is restricted with inter and intra-observer variability and inconsistency of results. This book, therefore, proposes an automated detection and measurement method for NT thickness. Artificial neural network was trained to locate the preferable region that contains NT. Border detection of NT based on Dynamic Programming algorithm is utilized to find the optimal thickness of the windowed region. Risk calculation is developed referring to delta-NT via maternal age and NT thickness. The system is designed and implemented using C++ programming environment. This should be especially useful for students, lecturers or professional researchers in biomedical and image processing fields.