Stochastic resonance aided robust techniques for segmentation of medical ultrasound images
Stochastic resonance aided robust techniques for segmentation of medical ultrasound images
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Date
2013-01-01
Authors
Sagar, J. V.R.
Bhagvati, Chakravarthy
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Abstract
The existence of stochastic resonance has been demonstrated in physical, biological and geological systems for boosting weak signals to make them detectable. Narrow regions, small features and low-contrast or subtle edges, in noisy images, correspond to such weak signals. In this paper, the occurrence and exploitation of stochastic resonance in the detection, extraction and analysis of such features is demonstrated both mathematically and empirically. The mathematical results are confirmed by simulation studies. Finally, results on medical ultrasound images demonstrate that several subtle features lost by the application of robust techniques such as mean shift filter are recovered by stochastic resonance. These results reconfirm the mathematical and simulation findings. © 2013 IEEE.
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Keywords
Asymptotic Mean Average Square Error,
Epanechnikov kerne,
Mean-Shift Filte,
Robust Techniques,
Signal-to-Noise Ratio,
Stochastic Resonance
Citation
2013 4th National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics, NCVPRIPG 2013