JCS_V1_N2_RP2 T. Surendra Nath V. Kalpana Vijaya Kishore Journal on Communication Engineering and Systems 2277-5242 1 2 6 11 Noise, Medical image, DICOM, Nodules, Classification, Morphology, Watershed Various medical imaging available are MRI, CT, US and DICOM. Automated Computer Aided Diagnosing (CAD) system detects lung cancer with improved diagnostic radiology. Several approaches to lung CAD combine geometric and intensity models to enhance local anatomical structure. Two difficulties those are primarily associated with the detection of nodules include the detection of nodules that are adjacent to vessels or the chest wall when they have very similar intensity; and the detection of nodules that are non-spherical in shape. In such cases, intensity thresholding or model based methods might fail to identify those nodules. In this paper Region of interest segmentation of DICOM lung image is performed in the noisy environment such as Poisson and speckle using morphology and watershed algorithm. The ROI lung area blood vessels and nodules from the major lung portion are extracted achieved using different edge detection operators such as Sobel, Prewitt and LoG in presence of noise. The results are helpful to study and analyse the influence of noises on the DICOM images in extracting region of interest. February - April 2012 Copyright © 2012 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=1770