Abstract
Feature selection is a processing step that gives a subset of features required for analyzing an image. The process flow of medical image processing includes pre-processing, image segmentation, feature extraction and feature selection. Medical imaging has been developed predominantly nowadays. It assists the physicians to diagnose the diseases through various medical modalities. Fetal defects are the most common congenital abnormality found at birth. Fetal features are selected and extracted to determine fetal biometrics such as Amniotic Fluid Volume, Bi-parietal Diameter, Head Circumference, Abdominal Circumference, Femur Length and Gestational Age. IntraUterine Growth Restriction remains a challenging problem for both the obstetrician and the pediatrician. The vital role of this approach is to detect abnormalities non-invasively and reduce the risk factors in early stages of pregnancy.
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Ramya, R., Srinivasan, K., Sharmila, B., Priya Dharshini, K. (2019). Feature Selection in Fetal Biometrics for Abnormality Detection in Ultrasound Images. In: Hemanth, J., Balas, V. (eds) Nature Inspired Optimization Techniques for Image Processing Applications. Intelligent Systems Reference Library, vol 150. Springer, Cham. https://doi.org/10.1007/978-3-319-96002-9_12
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