Open AccessLung Cancer Detection Using Marker Controlled Watershed with SVM
Author(s) -
Fatema Tuj Johora,
Mehdi Hassan Jony,
Shakhawat Hossain,
Humayun Kabir Rana
Publication year - 2018
Publication title -
gub journal of science and engineering
Language(s) - English
Resource type - Journals
ISSN - 2409-0476
DOI - 10.3329/gubjse.v5i1.47897
Subject(s) - support vector machine , lung cancer , matlab , cancer , artificial intelligence , computer science , pattern recognition (psychology) , feature (linguistics) , feature extraction , lung , feature vector , machine learning , medicine , pathology , linguistics , philosophy , operating system
Lung cancer is one of the most dangerous diseases and prediction of it, is the most challenging problem nowadays. Most of the cancer cells are overlapped with each other. It is hard to detect the cells but also essential to identify the presence of cancer cells in the early stage. Early detection of lung cancer may reduce the death rate. In this study, we used the Grey Level Co-occurrence Matrix (GLCM) to extract the feature of cancer affected lung image and then Support Vector Machine (SVM) has been used to detect normal and abnormal lung cells after implementing the features. Our experimental evaluation using MATLAB demonstrates the efficient performance of the proposed system and in the result.
GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 5(1), Dec 2018 P 24-30