Denoising of Medical Images Using Virtual Instrumentation
A.Umarani1, A.Asha2, M.V.Vandhana3, P.Nandhini4, B.Dhivya5
1Mrs. A. Umarani, Associate Professor Department of Electronics & Instrumentation Engineering, KLNCE, Madurai, India.
2A.Asha, Professor Department of Mechanical Engineering, KCET, Virudhunagar, India.
3M.V. Vandhana, Student in the Department of Electronics and Instrumentation Engineering, KLNCE, Madurai, India.
P. Nandhini Student in the Department of Electronics and Instrumentation Engineering, KLNCE, Madurai, India.
B. Dhivya, Student in the Department of Electronics and Instrumentation Engineering, KLNCE, Madurai, India.
Manuscript received on March 22, 2013. | Revised Manuscript received on April 15, 2013. | Manuscript published on April 30, 2013. | PP: 378-382 | Volume-2, Issue-4, April 2013. | Retrieval Number: D1450042413/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The medical image (CT angiographic images) we obtained from various devices is corrupted with noise. The obtained image needs processing before it can be used for any diagnosis. Low contrast and poor quality are the main problems in the production of medical images. Denoising is the process with which we reconstruct a signal from a noisy one. Image denoising involves the manipulation of the image data to produce a visually high quality image. Good quality image should have a less CNR value when compared to SNR. Developing Image denoising algorithms is a difficult operation because fine details in a medical image embedding diagnostic information should not be destroyed during noise removal. In this paper a comparative study of different types of noises at different level are done. We have determined qualitative and quantitative analysis using Laboratory Virtual Instrumentation Engineering Workbench.
Keywords: Noises, Angiography, LabVIEW.