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ROI Segmentation On DICOM Image In Presence Of Noise Based On Morphology

T. Surendra Nath*, V. Kalpana**, Vijaya Kishore***

* PG Student, Communication Systems, SITAMS, Chittoor

** PG Student, Communication Systems, SITAMS, Chittoor

*** Professor, Department of ECE, SITAMS, Chittoor

Periodicity:February - April'2012
DOI : https://doi.org/10.26634/jcs.1.2.1770

Abstract

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.

Keywords

Noise, Medical image, DICOM, Nodules, Classification, morphology, watershed

How to Cite this Article?

Nath, T. S., Kalpana, V., and Kishore, V. V. (2012). ROI Segmentation On DICOM Image In Presence Of Noise Based On Morphology. i-manager’s Journal on Communication Engineering and Systems, 1(2), 6-11. https://doi.org/10.26634/jcs.1.2.1770

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