• A.Jahnavi Reddy
• P.Pranitha
• Dr. R. Jegadeesan
• B.Sindhuja
• B.Manoj Kumar

Image processing techniques are currently commonly utilized in the therapeutic field for early detection of infections. This exploration expects to improve exactness, affectability, and explicitness of early detection of lung disease through a combination of image processing techniques and data mining. The Computed Tomography (CT) filter image of the lungs is pre-handled and the Region of Interest (ROI) sectioned, held and compressed utilizing a DWT (Discrete Waveform Transform) strategy. The subsequent ROI image is decomposed into four sub frequencies, groups LL, HL, LH, and HH. Once more, the LL sub recurrence is decomposed into four sub-groups, applying a 2-level DWT to the ROI based image. Further, highlights, for example, entropy, co-connection, vitality, change, and homogeneity are extricated from the 2-level DWT images utilizing a GLCM (Gray Level Co-occurrence Matrix) with characterization affected by methods for an SVM (Support Vector Machine). Order distinguishes whether the CT image is ordinary or carcinogenic. The Lung Image Database Consortium dataset (LIDC) has been utilized for preparing and testing reason for this examination. A Receiver Operating Characteristics (ROC) bend is utilized to break down the execution of the system. By and large, the system has a precision of 95.16%, affectability of 98.21% and explicitness of 78.69%.

Computer Aided Diagnosis System, optimal thresholding, gray level co-occurrence matrix (GLCM), Support vector machine (SVM) Receiver Operating Characteristics, Computed Tomography.

"A COMPARATIVE STUDY ON DETECTION OF LUNG TUMOR USING VARIOUS IMAGE DATA ANALYSIS AND CLASSIFIER METHODOLOGIES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.192-201, March-2019, Available :http://www.jetir.org/papers/JETIRAU06029.pdf

"A COMPARATIVE STUDY ON DETECTION OF LUNG TUMOR USING VARIOUS IMAGE DATA ANALYSIS AND CLASSIFIER METHODOLOGIES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp192-201, March-2019, Available at : http://www.jetir.org/papers/JETIRAU06029.pdf