Open AccessANALISIS JENIS PENYAKIT PARU-PARU BERDASARKAN CHEST X-RAY MENGGUNAKAN METODE FUZZY C-MEANS
Author(s) -
Fani Nur Azizah,
Dwi Juniati
Publication year - 2021
Publication title -
mathunesa: jurnal ilmiah matematika/mathunesa
Language(s) - English
Resource type - Journals
eISSN - 2716-506X
pISSN - 2301-9115
DOI - 10.26740/mathunesa.v9n2.p322-331
Subject(s) - canny edge detector , lung , segmentation , atelectasis , medicine , pneumothorax , artificial intelligence , computer science , pathology , edge detection , image (mathematics) , radiology , image processing
Lungs are vital organs that easily infected making them susceptible to diseases, such as atelectasis,effusion, pneumothorax and cancer. Diseases in the lungs can be detected using x-ray. Based onmedicaltheory, the results of the x-ray images of the lung diseases are difficult for ordinary people toread.. This research analyzes the x-ray image of the lungs to make easier the process of analysis. Theanalysis will be easy to carry out if the charaxteristic is known. In this case, fractal dimensions wereimplemented to clustering the typse if lung disesase based on chest x-ray. There are 100 x-ray image ofthe lungs that will be processed using segmentation. Result of segmentation is a region of the lungs.These regions are used in Canny edge detection to find out spots of lung disease. Then the dimensionvalue is calculated using box counting so that it can be clustered. The results of the experiment using thefuzzy c-means method with four clusters have an accuracy of 86%.
Keywords : Chest X-ray, Box Counting, Fuzzy C-Means