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Medical Decision Support System Using Pattern Recognition Methods for Assessment of Dermatoglyphic Indices and Diagnosis of Down’s Syndrome Read chapter Read first chapter

2014 | OriginalPaper | Chapter

An Adaptive Approach for Noise Reduction in Sequences of CT Images

Authors : Veska Georgieva, Roumen Kountchev, Ivo Draganov

Published in: Advanced Intelligent Computational Technologies and Decision Support Systems

Publisher: Springer International Publishing

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Abstract

CT presents images of cross-sectional slices of the body. The quality of CT images varies depending on penetrating X-rays in a different anatomically structures. Noise in CT is a multi-source problem and arises from the fundamentally statistical nature of photon production. This chapter presents an adaptive approach for noise reduction in sequences of CT images, based on the Wavelet Packet Decomposition and adaptive threshold of wavelet coefficients in the high frequency sub-bands of the shrinkage decomposition. Implementation results are given to demonstrate the visual quality and to analyze some objective estimation parameters such as PSNR, SNR, NRR, and Effectiveness of filtration in the perspective of clinical diagnosis.

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previous chapter Rule-Based Classification of Patients Screened with the MMPI Test in the Copernicus System
next chapter Intelligent Predictive Diagnosis on Given Practice Data Base: Background and Technique
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Metadata
Title
An Adaptive Approach for Noise Reduction in Sequences of CT Images
Authors
Veska Georgieva
Roumen Kountchev
Ivo Draganov
Copyright Year
2014
Book
Advanced Intelligent Computational Technologies and Decision Support Systems

Print ISBN: 978-3-319-00466-2

Electronic ISBN: 978-3-319-00467-9

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-00467-9_4

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