• Manisha A. Manjramkar

Lung is the complex organ that consists of spongy, elastic tissue equipped with structures that infuse our blood wifresh oxygen while ridding it of carbon-dioxide. Lung diseases are mainly occurred as airway disease, lung tissue disease and lung circulation disease are studied. In the computerized detection and classification of lung image five main methodologies are used. They are image preprocessing, segmentation, feature extraction, feature selection and classification. Automatic classification of lung diseases in computed tomography (CT) images is an important diagnostic tool for computer-aided diagnosis system. In this study, we propose a new image based feature extraction technique for classification of lung CT images. A novel fusion based method was developed by combining the Gabor filter and Walsh Hadamard transform features using median absolute deviation (MAD) technique and hence, it possesses the advantages of both models. The system has been tested with a number of real Computed Tomography lung images and has achieved satisfactory results in classifying the lung diseases.

Fusion, Pre-processing, feature extraction, feature selection, classification, genetic algorithm.

"A Literature Survey: A new fusion model for classification of the lung diseases using genetic algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.316-320, August-2018, Available :http://www.jetir.org/papers/JETIR1808795.pdf

"A Literature Survey: A new fusion model for classification of the lung diseases using genetic algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp316-320, August-2018, Available at : http://www.jetir.org/papers/JETIR1808795.pdf