Texture extraction: An evaluation of ridgelet, wavelet and co-occurrence based methods applied to mammograms

Expert Systems with Applications

Volumn 39, Issue 12, 2012, Pages 11036-11047

  Ramos, Rodrigo Pereira ^a   Nascimento, Marcelo Zanchetta Do ^b   Pereira, Danilo Cesar ^b  

^a UNIVERSIDADE FEDERAL DO VALE DO SÃO FRANCISCO   (Brazil)

^b UNIVERSIDADE FEDERAL DO ABC   (Brazil)

Author keywords

CADx; Co occurrence; Mammography; Texture extraction; Wavelet and ridgelet

Indexed keywords

CADX; CLASSIFICATION RATES; CLUSTER TENDENCY; CO-OCCURRENCE; CO-OCCURRENCE-MATRIX; COMPUTER-AIDED DETECTION; COMPUTER-AIDED DIAGNOSIS SYSTEM; DATA MINING TECHNIQUES; DATA SETS; DIGITIZED MAMMOGRAMS; FALSE-POSITIVE REDUCTION; GRAY LEVELS; IMAGE PROCESSING ALGORITHM; IMAGE TEXTURE ANALYSIS; MAMMOGRAPHIC; MAMMOGRAPHIC IMAGES; RANDOM FOREST ALGORITHM; REGIONS OF INTEREST; RIDGELET TRANSFORMS; RIDGELETS; TEXTURE CLASSIFICATION; TEXTURE DESCRIPTORS; TEXTURE EXTRACTION; TEXTURE PATTERNS; WAVELET-BASED FEATURE;

COMPUTER AIDED DIAGNOSIS; DATA MINING; DECISION TREES; GENETIC ALGORITHMS; IMAGE PROCESSING; MAMMOGRAPHY; TEXTURES; WAVELET TRANSFORMS; X RAY SCREENS;

FEATURE EXTRACTION;

EID: 84861198466     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2012.03.020     Document Type: Article

References (43)

1. Bovis, K.; Singh, S. (2000) Detection of masses in mammograms using texture features. In Proceedings of the 15th international conference on pattern recognition, 2, pp. 267-270.
2. L. Breiman Random forests Machine Learning 45 2001 5 32
3. E.J. Candès, and D.L. Donoho Ridgelets: A key to higher-dimensional intermittency? Philosophical Transactions of the Royal Society of London Series A-Mathematical Physical and Engineering Sciences 1999 2245 2509
4. S.R. Deans The Radon transform and some of its applications 1983 John Wiley and Sons New York
5. DeCoursey, W. J. (2003). Statistics and probability for engineering applications. Newnes.
6. L. Dettori, and L. Semler A comparison of wavelet, ridgelet and curvelet-based texture classification algorithms in computed tomography Computers in Biology and Medicine 37 2007 486 498
7. M.N. Do, and M. Vetterli The finite ridgelet transform for image representation IEEE Transactions on Image Processing 12 2003 16 28
8. M. Elter, and A. Horsch CADx of mammographic masses and clustered microcalcifications: A review Med. Phys. 36 2009 2052 2068
9. M. Elter, and A. Horsch CADx of mammographic masses and clustered microcalcifications: A review Medical Physics 36 2009 2052 2068
10. T. Fawcett An introduction to ROC analysis Pattern Recognition Letters 27 2006 861 874
11. Gonzalez, R.; Woods, R. (2002). Digital Image Processing, Addison-Wesley, 2nd Ed.
12. M. Gromet Comparison of computer-aided detection to double reading of screening mammograms: Review of 231,221 mammograms American Journal of Roentgenology 190 2008 854 859
13. S. Gupta, P.F. Chyn, and M.K. Markey Breast cancer CADx based on BI-RADS descriptors from two mammographic views Medical Physics 33 2006 1810 1817
14. S. Gupta, and M.K. Markey Correspondence in texture features between two mammographic views Medical Physics 32 2005 1598 1606
15. R.M. Haralick, K. Shanmugam, and Dinstein Textural features for image classification IEEE Transactions on Systems, Man, and Cybernetics 10 1973 610 621
16. M. Heath, K. Bowyer, D. Kopans, P. Kegelmeyer, R. Moore, and K. Chang Current status of the digital database for screening mammography Digital Mammography 1998 457 460
17. Instituto Nacional do Câncer (INCA), (2010). Estimativa da Incidência e Mortalidade por Câncer no Brasil. Available at http://www2.inca.gov.br/wps/wcm/connect/tiposdecancer/site/home/mama/ cancer-mama.
18. R. Kohavi, and F. Provost Glossary of terms Machine Learning 30 1998 271 274
19. W.K. Lim, and M.J. Er Classification of mammographic masses using generalized dynamic fuzzy neural networks Medical Physics 31 2004 1288 1295
20. S. Liu, C.F. Babbs, and E.J. Delp Multiresolution detection of spiculated lesions in digital mammograms IEEE Transactions on Image Processing 10 2001 874 884
21. X. Lladó, A. Oliver, J. Freixenet, R. Martí, and J. Martí A textural approach for mass false positive reduction in mammography Computerized Medical Imaging and Graphics 33 2009 415 422
22. Mallat, S. (1996). Wavelets for a Vision. In Proceedings of the IEEE, 84, pp. 604-614.
23. S. Mallat A wavelet tour of signal processing 2nd ed. 1999 Academic Press
24. M. Masotti, N. Lanconelli, and R. Campanini Computer-aided mass detection in mammography: False positive reduction via gray-scale invariant ranklet texture features Medical Physics 36 2009 311 316
25. M.E. Mavroforakis, H.V. Georgiou, N. Dimitropoulos, D. Cavouras, and S. Theodoridis Mammographic masses characterization based on localized texture and dataset fractal analysis using linear, neural and support vector machine classifiers Artificial Intelligence in Medicine 37 2006 145 162
26. M.A. Mazurowski, P.A. Habas, J.M. Zurada, and G.D. Tourassi Decision optimization of case-based computer-aided decision systems using genetic algorithm with application to mammography Physics in Medicine and Biology 53 2008 895 908
27. C.E. Metz Basic principles of roc analysis Seminars in Nuclear Medicine 8 1978 283 298
28. C.E. Metz, B.A. Herman, and J.H. Shen Maximum likelihood estimation of receiver operating characteristic (roc) curves from continuously-distributed data Statistics in Medicine 17 1998 1033 1053
29. F. Moayedi, Z. Azimifar, R. Boostani, and S. Katebi Contourlet-based mammography mass classification using the SVM family Computers in Biology and Medicine 40 2010 373 383
30. R. Mousa, Q. Munib, and A. Moussa Breast cancer diagnosis system based on wavelet analysis and fuzzy-neural Expert Systems with Applications 28 2005 713 723
31. N.R. Mudigonda, R.M. Rangayyan, and J.E. Desautels Detection of breast masses in mammograms by density slicing and texture flow-field analysis IEEE Transactions on Medical Imaging 20 2001 1215 1227
32. A. Oliver, J. Freixenet, J. Martí, E. Pérez, J. Pont, and E.R.E. Denton A review of automatic mass detection and segmentation in mammographic images Medical Image Analysis 14 2010 87 110
33. S. Paquerault, N. Petrick, H.P. Chan, B. Sahiner, and M.A. Helvie Improvement of computerized mass detection on mammograms: Fusion of two-view information Medical Physics 29 2002 238 247
34. W. Qian, X. Sun, D. Song, and R.A. Clark Digital mammography: Wavelet transform and Kalman-filtering neural network in mass segmentation and detection Academic Radiology 8 2001 1074 1082
35. E.A. Rashed, I.A. Ismail, and S.I. Zaki Multiresolution mammogram analysis in multilevel decomposition Pattern Recognition Letters 28 2007 286 292
36. B. Sahiner, H.P. Chan, N. Petrick, M.A. Helvie, and L.M. Hadjiiski Improvement of mammographic mass characterization using spiculation measures and morphological features Medical Physics 28 2001 1455 1465
37. B. Sahiner, H.P. Chan, D. Wei, N. Petrick, M.A. Helvie, and D.D. Adler Image feature selection by a genetic algorithm: Application to classification of mass and normal breast tissue Medical Physics 23 1996 1671 1684
38. S. Selvan, and S. Ramarishnan SVD-based modeling for image texture classification using wavelet transformation IEEE Transactions on Image Processing 16 2007 2688 2696
39. Selvi, S. T.; Malmathanraj, R. (2006). Segmentation and SVM Classification of Mammograms. In Proceedings of the IEEE International Conference on Industrial Technology, pp. 905-910.
40. Semler, L.; Dettori, L.; Kerr, W. (2006). Ridgelet-based texture classification in computed tomography. In Proceedings in the eighth IASTED international conference on signal and image processing, Honolulu.
41. J.L. Starck, M. Elad, and D.L. Donoho Redundant multiscale transforms and their application for morphological component analysis Advances in Imaging and Electron Physics 132 2004 287 348
42. J. Tang, R.M. Rangayyan, J. Xu, N. El, and Y. Yang Computer-aided detection and diagnosis of breast cancer with mammography: Recent advances IEEE Transactions on Information Technology in Biomedicine 13 2009 236 251
43. L. Vibha, G.M. Harshavardhan, K. Pranaw, P. Deepa Shenoy, K.R. Venugopal, and M.P. Lalit Classification of mammograms using decision trees IDEAS 2006 263 266