000 06677nam a2200745 i 4500
001 6813410
003 IEEE
005 20200413152859.0
006 m eo d
007 cr cn |||m|||a
008 101209s2011 caua foab 000 0 eng d
020 _a9781608450305 (electronic bk.)
020 _z9781608450299 (pbk.)
024 7 _a10.2200/S00301ED1V01Y201010BME038
_2doi
035 _a(CaBNVSL)gtp00545391
035 _a(OCoLC)695498507
040 _aCaBNVSL
_cCaBNVSL
_dCaBNVSL
050 4 _aRG493.5.R33
_bA972 2011
060 4 _aWP 815
_bA972a 2011
082 0 4 _a618.1907572
_222
100 1 _aAyres, Fábio J.
245 1 0 _aAnalysis of oriented texture
_h[electronic resource] :
_bwith applications to the detection of architectural distortion in mammograms /
_cFábio J. Ayres, Rangaraj M. Rangayyan, J.E. Leo Desautels.
260 _aSan Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) :
_bMorgan & Claypool,
_cc2011.
300 _a1 electronic text (xi, 148 p.) :
_bill., digital file.
490 1 _aSynthesis lectures on biomedical engineering,
_x1930-0336 ;
_v# 38
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat Reader.
500 _aPart of: Synthesis digital library of engineering and computer science.
500 _aSeries from website.
504 _aIncludes bibliographical references (p. 129-146).
505 0 _a1. Detection of oriented features in images -- Oriented features in images -- Directionally sensitive filters -- Steerable filters -- Gabor filters -- Line operator -- Frequency-domain analysis -- Performance analysis of the oriented feature detectors -- Performance in terms of detection and angular accuracy -- Analysis of performance with multiscale features -- Computational time -- Discussion -- Robustness to noise and scale -- Angular accuracy -- Computational speed -- Application of Gabor filters to the detection of curvilinear structures in mammograms -- Remarks --
505 8 _a2. Analysis of oriented patterns using phase portraits -- Phase portraits -- Analysis of orientation fields using phase portraits -- Local analysis of orientation fields -- Analysis of large orientation fields -- Illustrative examples -- Synthetic test images -- Analysis of a mammographic ROI -- Remarks --
505 8 _a3. Optimization techniques -- Introduction -- The optimization problem -- Optimization procedures -- Linear least-squares -- Iterative linear least-squares -- Nonlinear least-squares -- Simulated annealing -- Particle swarm optimization -- Comparative analysis of the optimization procedures -- Remarks --
505 8 _a4. Detection of sites of architectural distortion in mammograms -- The first method -- Filtering and downsampling the orientation field -- Post-processing of the node map and detection in the first method -- Results of the first method -- The second method -- Removal of the DC component in the Gabor filters -- Selection of curvilinear structures -- Filtering and downsampling the orientation field -- Estimating the phase portrait maps -- Detection of architectural distortion -- Results of the second method -- The third method -- Adoption of a symmetric matrix A -- Vote casting and detection -- Results of the third method -- Remarks --
505 8 _aA. Computer-aided diagnosis of breast cancer -- A.1. Screening for breast cancer -- A.2. Mammographic signs of breast cancer -- A.3. Enhancement of mammograms -- A.4. Segmentation of mammograms and analysis of breast density -- A.5. Detection and classification of microcalcifications -- A.6. Detection and classification of masses -- A.7. Analysis of curvilinear structures -- A.8. Analysis of bilateral asymmetry -- A.9. Detection of architectural distortion -- A.10. Analysis of prior mammograms -- A.11. Full-field digital mammography -- A.12. Indexed atlases, data mining, and content-based retrieval -- A.13. Computer-aided diagnosis of breast cancer -- A.14. Remarks --
505 8 _aB. Event detection in medical images -- B.1. Sensitivity and specificity -- B.2. Receiver operating characteristic analysis -- Bibliography -- Authors' biographies.
506 1 _aAbstract freely available; full-text restricted to subscribers or individual document purchasers.
510 0 _aCompendex
510 0 _aINSPEC
510 0 _aGoogle scholar
510 0 _aGoogle book search
520 3 _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.
530 _aAlso available in print.
588 _aTitle from PDF t.p. (viewed on December 9, 2010).
650 0 _aBreast
_xRadiography.
650 0 _aImage processing
_xDigital techniques.
650 0 _aOptical pattern recognition.
650 1 2 _aMammography.
650 1 2 _aBreast Neoplasms.
653 _aOriented texture
653 _aArchitectural distortion
653 _aMammography
653 _aBreast cancer
653 _aGabor filters
653 _aPhase portraits
653 _aLine detectors
653 _aOptimization techniques
653 _aComputer-aided diagnosis
700 1 _aRangayyan, Rangaraj M.
700 1 _aDesautels, J. E. Leo.
776 0 8 _iPrint version:
_z9781608450299
830 0 _aSynthesis digital library of engineering and computer science.
830 0 _aSynthesis lectures on biomedical engineering,
_x1930-0336 ;
_v# 38.
856 4 2 _3Abstract with links to resource
_uhttp://ieeexplore.ieee.org/servlet/opac?bknumber=6813410
999 _c561794
_d561794