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  2. Volume 7, Issue 9
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Online ISSN: 2515-8260

Volume7, Issue9

CT LUNG IMAGES CLASSIFICATION FOR NODULE DETECTION

    R. Charanya J. Josphin Mary

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 9, Pages 1390-1393
10.31838/ejmcm.07.09.143

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Abstract

Lung cancer is an early lung cancer. The world's greatest cause of death is lung cancer. Lung cancer typically does not cause signs or symptoms in its early stages. In order to reduce the mortality rate early detection of lung cancer is required. Computed Tomography (CT) lung images classification for nodule detection is discussed in this study. At first energy features are used for feature extraction. Then maximum likelihood classifier is used for classification. The experimental results show the performance of pulmonary nodules classification in terms of accuracy.
Keywords:
    pulmonary nodules CT lung image Maximum likihood Classification
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(2020). CT LUNG IMAGES CLASSIFICATION FOR NODULE DETECTION. European Journal of Molecular & Clinical Medicine, 7(9), 1390-1393. doi: 10.31838/ejmcm.07.09.143
R. Charanya; J. Josphin Mary. "CT LUNG IMAGES CLASSIFICATION FOR NODULE DETECTION". European Journal of Molecular & Clinical Medicine, 7, 9, 2020, 1390-1393. doi: 10.31838/ejmcm.07.09.143
(2020). 'CT LUNG IMAGES CLASSIFICATION FOR NODULE DETECTION', European Journal of Molecular & Clinical Medicine, 7(9), pp. 1390-1393. doi: 10.31838/ejmcm.07.09.143
CT LUNG IMAGES CLASSIFICATION FOR NODULE DETECTION. European Journal of Molecular & Clinical Medicine, 2020; 7(9): 1390-1393. doi: 10.31838/ejmcm.07.09.143
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