Abstract
Diagnostic imaging is an invaluable tool in medicine. Different methods of getting images like Gamma Ray Imaging, X-Ray Imaging, Magnetic resonance imaging (MRI), Computed Tomography (CT), Digital Mammography, and other imaging modalities provide an effective means for noninvasive mapping the anatomy of a subject. These technologies have greatly increased knowledge of normal and diseased anatomy for medical research and are a critical component in diagnosis and treatment planning. With the limitation of number of exposures for Gamma Ray or X-Rays to the patient, it is difficult to see the critical feature if the intensity/brightness/ contrast are not proper. Moreover the growing size and number of these medical images have necessitated the use of computers to facilitate processing and analysis. In particular, computer algorithms for the intensity/ brightness/contrast adjustment, delineation of anatomical structures and other regions of interest are becoming increasingly important in assisting and automating specific radiological tasks.
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Kulkarni, D.A., Dere, P.U. (2011). Characterization of cardiomegaly disease from x-ray images using mean shift based image segmentation. In: Pise, S.J. (eds) Thinkquest~2010. Springer, New Delhi. https://doi.org/10.1007/978-81-8489-989-4_24
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DOI: https://doi.org/10.1007/978-81-8489-989-4_24
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-8489-988-7
Online ISBN: 978-81-8489-989-4
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