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020 _a9783031015243
_9978-3-031-01524-3
024 7 _a10.1007/978-3-031-01524-3
_2doi
050 4 _aTK5102.9
072 7 _aTJF
_2bicssc
072 7 _aUYS
_2bicssc
072 7 _aTEC067000
_2bisacsh
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_2thema
072 7 _aUYS
_2thema
082 0 4 _a621,382
_223
100 1 _aLoizou, Christos P.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983943
245 1 0 _aDespeckle Filtering for Ultrasound Imaging and Video, Volume II
_h[electronic resource] :
_bSelected Applications, Second Edition /
_cby Christos P. Loizou, Constantinos S. Pattichis.
250 _a2nd ed. 2015.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXXIV, 156 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Algorithms and Software in Engineering,
_x1938-1735
505 0 _aPreface -- List of Symbols -- List of Abbreviations -- Introduction and Review of Despeckle Filtering -- Segmentation of the Intima-media Complex and Plaque in CCA Ultrasound Imaging and Video Following Despeckle Filtering -- Evaluation of Despeckle Filtering of Carotid Plaque Imaging and Video Based on Texture Analysis -- Wireless Video Communication Using Despeckle Filtering and HVEC -- Summary and Future Directions -- References -- Authors' Biographies .
520 _aIn ultrasound imaging and video visual perception is hindered by speckle multiplicative noise that degrades the quality. Noise reduction is therefore essential for improving the visual observation quality or as a pre-processing step for further automated analysis, such as image/video segmentation, texture analysis and encoding in ultrasound imaging and video. The goal of the first book (book 1 of 2 books) was to introduce the problem of speckle in ultrasound image and video as well as the theoretical background, algorithmic steps, and the MatlabTM for the following group of despeckle filters: linear despeckle filtering, non-linear despeckle filtering, diffusion despeckle filtering, and wavelet despeckle filtering. The goal of this book (book 2 of 2 books) is to demonstrate the use of a comparative evaluation framework based on these despeckle filters (introduced on book 1) on cardiovascular ultrasound image and video processing and analysis. More specifically, the despeckle filtering evaluation framework is based on texture analysis, image quality evaluation metrics, and visual evaluation by experts. This framework is applied in cardiovascular ultrasound image/video processing on the tasks of segmentation and structural measurements, texture analysis for differentiating between two classes (i.e. normal vs disease) and for efficient encoding for mobile applications. It is shown that despeckle noise reduction improved segmentation and measurement (of tissue structure investigated), increased the texture feature distance between normal and abnormal tissue, improved image/video quality evaluation and perception and produced significantly lower bitrates in video encoding. Furthermore, in order to facilitate further applications we have developed in MATLABTM two different toolboxes that integrate image (IDF) and video (VDF) despeckle filtering, texture analysis, and image and video quality evaluation metrics. The code for these toolsets is open source and these are available to download complementary to the two monographs.
650 0 _aSignal processing.
_94052
650 1 4 _aSignal, Speech and Image Processing.
_931566
700 1 _aPattichis, Constantinos S.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983944
710 2 _aSpringerLink (Online service)
_983945
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031003967
776 0 8 _iPrinted edition:
_z9783031026522
830 0 _aSynthesis Lectures on Algorithms and Software in Engineering,
_x1938-1735
_983946
856 4 0 _uhttps://doi.org/10.1007/978-3-031-01524-3
912 _aZDB-2-SXSC
942 _cEBK
999 _c85588
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