A Novel Framework for Fetal Nuchal Translucency Abnormality Detection Using Hybrid Maxpool Matrix Histogram Analysis - Verma, Deepti; Agrawal, Shweta (Computer Assisted Methods in Engineering and Science; Vol 30 No 3 (2023), 2023)
Birth defects affect 1 to 3 percent of the population and are mostly detected in pregnant women through double, triple, and quadruple testing. Ultrasonography helps to discover and define such anomalies in fetuses. Ultrasound pictures of nuchal translucency (NT) are routinely used to detect genetic disorders in fetuses. The NT area lacks identifiable local behaviors and detection algorithms are required to classify the fetal head. On the other hand, explicit identification of other body parts comes at a higher cost in terms of annotations, implementation, and analysis. In circumstances of ambiguous head placement or non-standard head-NT relationships, it may potentially cause cascading errors. In this research work, a linear contour size filter is used to decrease noise from the image, and then the picture is scaled. Then, a novel hybrid maxpool matrix histogram analysis (HMMHA) is proposed to enhance the initiation and progression. The training and assessment were conducted using a dataset of 33 ultrasound pictures. Extensive testing shows that the direct method reliably identifies and measures NT. The suggested model may assist doctors in making decisions about pregnancies with fetal growth restriction, particularly for patients who have nuchal translucency or congenital anomalies and do not require induced labor due to these abnormalities. The performance of the proposed technique is analyzed in terms of error rate, sensitivity, Matthews correlation coefficient (MCC), accuracy, precision, recall, and F1-score. The error rate of the proposed model is 28.21% and it is found to be better when compared with the conventional approaches. Finally, the error prediction is compared with the existing models obtained from the medical dataset of pregnant women to identify fetal abnormality positions.