Fetal head periphery extraction from ultrasound image using jaya algorithm and Chan-Vese segmentation

In recent years, a considerable advancement can be seen in medical image examination. The proposed work implements a Hybrid-Scheme (HS) to determine the Fetal-Head-Circumference (FHC) section from the chosen Two-Dimensional Ultrasound Image (2DUI). Normally, the 2DUI analysis is widely implemented to supervise the development of the fetus. This study implements a combination of an image pre-processing plus post-processing practice to mine FHC from the 2DUI. This pre-processing implements the Jaya-Algorithm (JA) and Otsu’s threshold and post-processing implements Chan-Vese (CV) and Level-Set (LS) segmentation. In this work, FHC extraction process is performed with and without pre-processing procedure. After extracting the head section from the chosen 2DUI, the supremacy of executed tool is next appraised by employing a qualified study between mined region and its associated ground-truth. Further, the Haar features are extracted and its values are later evaluated with the ground-truth picture. The results of experimental work substantiate that, the hybrid procedure is capable in examining the 2DUI and offers enhanced picture similarity measures (>88.5%) during the FHC examination.