Teknik Segmentasi untuk Mengidentifikasi Kelainan Jantung pada Citra Rontgen Dada
DOI:
https://doi.org/10.35134/komtekinfo.v9i3.307Keywords:
Heart Defects, Segmentation, Identification, X-rays Image, KaggleAbstract
The annual death toll from heart disease is 17.5 million people. Currently, heart disease is a prevalent condition that kills a lot of people and shortens people's lives. Life is based on the work of the heart, since the heart is a much-needed part of our body where life is impossible. Heart disease affects heart function and can lead to death or annoy the patient before deathThe use of contemporary medical imaging methods like computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI), as well as X-rays, is now commonplace. These methods enable non-invasive qualitative and quantitative assessment of the anatomical structure and function of the heart and support diagnosis, disease monitoring, treatment planning, and prognosis. The purpose of this study is to find heart problems in patients. The data used in this study were chest X-rays of patients with normal heart conditions and chest X-rays of abnormal heart patients obtained from the kaggle website. Segmentation techniques are used to process these cardiac images. Segmentation is the process of separating between an object and another object or between objects and the background contained in an image. Then the calculation of the area of the heart area is carried out using the extraction of morpological and regional features method characteristics with an algorithm that has been developed. The results of this study can identify heart defects through the process of measuring the area of the heart normal and abnormal. So that it produces a good accuracy rate of 85%. This segmentation technique is proven to be very good so that it can be a medical reference to perform further medical actions against abnormalities in the heart.
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