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008			230204s2015 sz | s |||| 0|eng d
020			_a9783031015236
024	7		_a10.1007/978-3-031-01523-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQC427.8.S64 _b2015 EB
100	1		_aLoizou, Christos P., _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686561 _d1962-
245	1	0	_aDespeckle Filtering for Ultrasound Imaging and Video, Volume I : _bAlgorithms and Software, Second Edition _cby Christos P. Loizou, Constantinos S. Pattichis
250			_a2nd edition 2015
264		1	_aCham _bSpringer International Publishing _c2015
300			_a1 recurso en línea (XXV, 154 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Algorithms and Software in Engineering _x1938-1735
505	0		_aPreface -- Acknowledgments -- List of Symbols -- List of Abbreviations -- Introduction to Speckle Noise in Ultrasound Imaging and Video -- Basics of Evaluation Methodology -- Linear Despeckle Filtering -- Nonlinear Despeckle Filtering -- Diffusion Despeckle Filtering -- Wavelet Despeckle Filtering -- Evaluation of Despeckle Filtering -- Summary and Future Directions -- References -- Authors' Biographies .
520			_aIt is well known that speckle is a multiplicative noise that degrades image and video quality and the visual expert's evaluation in ultrasound imaging and video. This necessitates the need for robust despeckling image and video techniques for both routine clinical practice and tele-consultation. The goal for this book (book 1 of 2 books) is to introduce the problem of speckle occurring in ultrasound image and video as well as the theoretical background (equations), the algorithmic steps, and the MATLABTM code for the following group of despeckle filters: linear filtering, nonlinear filtering, anisotropic diffusion filtering, and wavelet filtering. This book proposes a comparative evaluation framework of these despeckle filters based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts. Despeckle noise reduction through the application of these filters will improve the visual observation quality or it may be used as a pre-processing step for further automated analysis, such as image and video segmentation, and texture characterization in ultrasound cardiovascular imaging, as well as in bandwidth reduction in ultrasound video transmission for telemedicine applications. The aforementioned topics will be covered in detail in the companion book to this one. 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 books. Table of Contents: Preface / Acknowledgments / List of Symbols / List of Abbreviations / Introduction to Speckle Noise in Ultrasound Imaging and Video / Basics of Evaluation Methodology / Linear Despeckle Filtering / Nonlinear Despeckle Filtering / Diffusion Despeckle Filtering / Wavelet Despeckle Filtering / Evaluation of Despeckle Filtering / Summary and Future Directions / References / Authors' Biographies.
988			_aSynthesis Collection of Technology_2015
650		7	_2embne _9139972 _aDiagnóstico por imagen
650		7	_2embne _9141162 _aAlgoritmos
700			_aPattichis, Constantinos S. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _999283
776	0	8	_iPrinted edition: _z9783031003950
776	0	8	_iPrinted edition: _z9783031026515
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01523-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _eIG _zSI