By Hubert Wojtowicz, Wieslaw Wajs (auth.), Barna Iantovics, Roumen Kountchev (eds.)
This booklet bargains a cutting-edge assortment masking subject matters regarding Advanced clever Computational applied sciences and determination help Systems that are utilized to fields like healthcare supporting the people in fixing difficulties. The publication brings ahead a wealth of principles, algorithms and case reviews in issues like: clever predictive prognosis; clever studying of clinical pictures; new layout for coding of unmarried and sequences of clinical photographs; clinical determination help structures; prognosis of Down’s syndrome; computational views for digital fetal tracking; effective compression of CT pictures; adaptive interpolation and halftoning for clinical photographs; purposes of man-made neural networks for real-life difficulties fixing; current and views for digital Healthcare checklist structures; adaptive ways for noise relief in sequences of CT photographs etc.
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So by setting these small coefficients to zero, will be eliminated much of the noise in the image. In this chapter, we purpose to reduce the noise components in the CT images on the base of 2D wavelet packet transformations. To improve the diagnostic quality of the medical objects some parameters of the wavelet transforms are optimized such as: determination of best shrinkage decomposition, threshold of the wavelet coefficients and value of the penalized parameter of the threshold. This can be made adaptively for which image in the sequence on the base of calculation and estimation of some objective parameters.
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