000 03751nam a22005295i 4500
001 978-3-031-01647-9
003 DE-He213
005 20240730164900.0
007 cr nn 008mamaa
008 220601s2011 sz | s |||| 0|eng d
020 _a9783031016479
_9978-3-031-01647-9
024 7 _a10.1007/978-3-031-01647-9
_2doi
050 4 _aT1-995
072 7 _aTBC
_2bicssc
072 7 _aTEC000000
_2bisacsh
072 7 _aTBC
_2thema
082 0 4 _a620
_223
100 1 _aAyres, Fábio J.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_986504
245 1 0 _aAnalysis of Oriented Texture with application to the Detection of Architectural Distortion in Mammograms
_h[electronic resource] /
_cby Fábio J Ayres, Rangaraj M Rangayyan, J. E. Leo Desautels.
250 _a1st ed. 2011.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2011.
300 _aXII, 150 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 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.
650 0 _aEngineering.
_99405
650 0 _aBiophysics.
_94093
650 0 _aBiomedical engineering.
_93292
650 1 4 _aTechnology and Engineering.
_986505
650 2 4 _aBiophysics.
_94093
650 2 4 _aBiomedical Engineering and Bioengineering.
_931842
700 1 _aRangayyan, Rangaraj M.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_986506
700 1 _aDesautels, J. E. Leo.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_986508
710 2 _aSpringerLink (Online service)
_986509
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031005190
776 0 8 _iPrinted edition:
_z9783031027758
830 0 _aSynthesis Lectures on Biomedical Engineering,
_x1930-0336
_986511
856 4 0 _uhttps://doi.org/10.1007/978-3-031-01647-9
912 _aZDB-2-SXSC
942 _cEBK
999 _c85966
_d85966