Improved segmentation of cardiac image using triangle and partial Monte Carlo

Abstract

In this paper, the segmentation of cardiac image for heart diseases is proposed. The method used Median High Boost Filter, Triangle Equation and Partial Monte Carlo. The first step is applying Median High Boost filter to eliminate noise. The second step is Triangle Equation to detect cardiac cavity and reconstruct the imprecise border. The third step is Partial Monte Carlo to measure the area of the heart cavity. This research used ultrasound to measure cardiac function. The experiments represented that the extended method is able to detect and improve the segmentation of cardiac cavity images with precise and faster. The performance segmentation for assessment errors cardiac cavity obtained an average triangle 8.18%, snake 19.94% and watershed 15.97%.