ANFIS classifier based Lung Tumor and Lymph node differentiation using Computer Tomography |
Author(s): |
| M. KAVITHA , MUTHAYAMMAL ENGINEERING COLLEGE, RASIPURAM; T.RAJA, MUTHAYAMMAL ENGINEERING COLLEGE |
Keywords: |
| Computerized Tomography (CT), Local Binary Pattern (LBP), Gray Level features, Adaptive Neural Fuzzy Inference System (ANFIS) classifier. |
Abstract |
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Analysis of primary lung tumors and disease is important for lung cancer staging and an automated system that can detect both types of abnormalities will be helpful for clinical routine. In this project, we present a new method to automatically detect both tumors and abnormal nodes simultaneously using Computerized Tomography (CT) thoracic images. We perform the detection of abnormalities, and then differentiate between tumors and lymph nodes using ANFIS classifier. Then lung tumors are classified as benign and malignant using this classifier. Moreover compared to several state-of-the-art methods (LapRLS, mcSVM, ESRC, mSRC, CBIR), the proposed ANFIS classifier can achieve significant improvement (mean accuracy of 93%, precision of 88%, recall of 94%, etc). |
Other Details |
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Paper ID: IJSRDV2I2019 Published in: Volume : 2, Issue : 2 Publication Date: 01/05/2014 Page(s): 140-143 |
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