Optimization of Fetal Development Measurement on Ultrasound Images Using Segmentation Techniques Combined

Fetal development needs to be carried out to determine the condition of the fetus in pregnant women. Detection of fetal development can be done using a medical tool called Ultrasonography (USG). Ultrasound images produce color images with varying levels of gray. The problem that occurs in detecting fetal development at this time is that the detection process carried out by medical personnel in identifying fetal development in ultrasound images is still not optimal. Given these shortcomings, image processing is needed to handle problems in the process of measuring fetal development. This research aims to measure fetal development using the image segmentation process. The segmentation process was carried out using thresholding techniques and image morphology, and measurements were continued using the Iterative Randomized Hough Transform (IRHT) algorithm. This research uses test data of 35 ultrasound images in Joint Photographic Experts Group (JPEG) format. Based on the tests that have been carried out, the segmentation process using thresholding and morphology techniques can provide an accuracy of 91.16%. With these results, this research has contributed to minimizing errors, increasing measurement accuracy, and providing a stronger basis for making decisions about fetal development.