000			03556nam a22004335i 4500
999			_c386824 _d386824
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003			ES-MaUEC
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007			cr nn 008mamaa
008			220601s2011 sz | s |||| 0|eng d
020			_a9783031016479
024	7		_a10.1007/978-3-031-01647-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA1637 _b2011 EB
100	1		_aAyres, Fábio José, _d1975- _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686110
245	1	0	_aAnalysis of Oriented Texture with application to the Detection of Architectural Distortion in Mammograms _cby Fábio J Ayres, Rangaraj M Rangayyan, J. E. Leo Desautels
250			_a1st edition 2011
264		1	_aCham _bSpringer International Publishing _c2011
300			_a1 recurso en línea (XII, 150 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Biomedical Engineering _x1930-0336
505	0		_aDetection of Oriented Features in Images -- Analysis of Oriented Patterns Using Phase Portraits -- Optimization Techniques -- Detection of Sites of Architectural Distortion in Mammograms.
520			_aThe presence of oriented features in images often conveys important information about the scene or the objects contained; the analysis of oriented patterns is an important task in the general framework of image understanding. As in many other applications of computer vision, the general framework for the understanding of oriented features in images can be divided into low- and high-level analysis. In the context of the study of oriented features, low-level analysis includes the detection of oriented features in images; a measure of the local magnitude and orientation of oriented features over the entire region of analysis in the image is called the orientation field. High-level analysis relates to the discovery of patterns in the orientation field, usually by associating the structure perceived in the orientation field with a geometrical model. This book presents an analysis of several important methods for the detection of oriented features in images, and a discussion of the phase portrait method for high-level analysis of orientation fields. In order to illustrate the concepts developed throughout the book, an application is presented of the phase portrait method to computer-aided detection of architectural distortion in mammograms. Table of Contents: Detection of Oriented Features in Images / Analysis of Oriented Patterns Using Phase Portraits / Optimization Techniques / Detection of Sites of Architectural Distortion in Mammograms.
988			_aSynthesis Collection of Technology_2011
650		7	_2embne _9147244 _aMamografía
650		7	_2embne _9305596 _aDiagnóstico por imagen _xTécnicas digitales
700	1		_aRangayyan, Rangaraj M. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686111
700	1		_aDesautels, J. E. Leo _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9783031005190
776	0	8	_iPrinted edition: _z9783031027758
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01647-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2023 _dz _esc _zSI