Anatomical structure characterization of fetal ultrasound images using texture-based segmentation technique via an interactive MATLAB application

Abstract

Objective: To describe the texture characteristics in several anatomical structures within fetal ultrasound images by applying an image segmentation technique through an application developed in MATLAB mathematical processing software. Methods: Prospective descriptive observational study with an analytical component. 2D fetal ultrasound images were acquired in patients admitted to the Maternal Fetal Medicine Unit of the Hospital de San José, Bogotá-Colombia. These images were loaded into the developed application to carry out the segmentation and characterization stages by means of 23 numerical texture descriptors. The data were analyzed with central tendency measures and through an embedding process and Euclidean distance. Results: Forty ultrasound images were included, characterizing 54 structures of the fetal placenta, skull, thorax, and abdomen. By embedding the descriptors, the differentiation of biologically known structures as distinct was achieved, as well as the non-differentiation of similar structures, evidenced using 2D and 3D graphs and numerical data with statistical significance. Conclusion: The texture characterization of the labeled structures in fetal ultrasound images through the numerical descriptors allows the accurate discrimination of these structures.