A textural approach for mass false positive reduction in mammography

Computerized Medical Imaging and Graphics

Volumn 33, Issue 6, 2009, Pages 415-422

  Llado X ^a   Oliver, A ^a   Freixenet, J ^a   Marti R ^a   Marti J ^a  

^a UNIVERSITY OF GIRONA   (Spain)

Author keywords

Breast cancer; False positive reduction; Image analysis; Local binary patterns; Mammographic automatic mass detection; Textural information

Indexed keywords

BREAST CANCER; FALSE POSITIVE REDUCTION; LOCAL BINARY PATTERNS; MAMMOGRAPHIC AUTOMATIC MASS DETECTION; TEXTURAL INFORMATION;

IMAGE ANALYSIS; SUPPORT VECTOR MACHINES;

CONTENT BASED RETRIEVAL;

ARTICLE; DATA BASE; FALSE POSITIVE RESULT; HISTOGRAM; IMAGE ANALYSIS; IMAGE PROCESSING; INFORMATION PROCESSING; LOCAL BINARY PATTERN; MAMMOGRAPHY; PARENCHYMA; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE;

ADULT; ALGORITHMS; BREAST NEOPLASMS; FALSE POSITIVE REACTIONS; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAMMOGRAPHY;

EID: 67349257490     PISSN: 08956111     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compmedimag.2009.03.007     Document Type: Article

References (45)

1. Eurostat, Health statistics Atlas on mortality in the European Union, Office for Official Publications of the European Union; 2002.
2. American Cancer Society Breast cancer: facts and figures. ACS; 2003-2004.
3. Esteve J., Kricker A., Ferlay J., and Parkin D. Facts and figures of cancer in the European Community. Tech. rep., International Agency for Research on Cancer. Lyon, France (1993)
4. Buseman S., Mouchawar J., Calonge N., and Byers T. Mammography screening matters for young women with breast carcinoma. Cancer 97 2 (2003) 352-358
5. Sickles E.A. Breast cancer screening outcomes in women ages 40-49: clinical experience with service screening using modern mammography. J Natl Cancer Inst: Monogr 22 (1997) 99-104
6. De Koning H.J., Fracheboud J., Boer R., Verbeek A.L., Collette H.J., and Hendriks J.H.C.L. Nation-wide breast cancer screening in the Netherlands: support for breast cancer mortality reduction. National evaluation team for breast cancer screening, Int J Cancer 60 6 (1995) 777-780
7. Hendee W.R., Beam C., and Hendrick E. Proposition: all mammograms should be double-read. Med Phys 26 (1999) 115-118
8. Thurfjell E.L., Lernevall K.A., and Taube A.A.S. Benefit of independent double reading in a population-based mammography screening program. Radiology 191 (1994) 241-244
9. Vacek P.M., Geller B.M., Weaver D.L., and Foster R.S. Increased mammography use and its impact on earlier breast cancer detection in Vermont. Cancer 94 8 (2002) 2160-2168
10. Bird R.E., Wallace T.W., and Yankaskas B.C. Analysis of cancers missed at screening mammography. Radiology 184 (1992) 613-617
11. Birdwell R.L., Ikeda D.M., O'Shaughnessy K.D., and Sickles E.A. Mammographic characteristics of 115 missed cancers later detected with screening mammography and the potential utility of computer-aided detection. Radiology 219 (2001) 192-202
12. Basset L.W., and Gold R.H. Breast Cancer Detection: Mammograms and Other Methods in Breast Imaging (1987), Grune & Stratton, New York
13. Hall F.M., Storella J.M., Siverstond D.Z., and Wyshak G. Nonpalpable breast lesions: recommendations for biopsy based on suspicion of carcinoma at mammography. Radiology 167 (1988) 353-358
14. Winsberg F., Elkin M., Macy J., Bordaz V., and Weymouth W. Detection of radiographic abnormalities in mammograms by means of optical scanning and computer analysis. Radiology 89 2 (1967) 211-215
15. Freer T.W., and Ulissey M.J. Screening mammography with computer-aided detection: prospective study of 12860 patients in a community breast center. Radiology 220 (2001) 781-786
16. Zwiggelaar R., Astley S.M., Boggis C.R.M., and Taylor C.J. Linear structures in mammographic images: detection and classification. IEEE Trans Med Imag 23 9 (2004) 1077-1086
17. Khoo L.A.L., Taylor P., and Given-Wilson R.M. Computer-aided detection in the United Kingdom national breast screening programme: prospective study. Radiology 237 2 (2005) 444-449
18. Nishikawa R.M., and Kallergi M. Computer-aided detection, in its present form, is not an effective aid for screening mammography. Med Phys 33 (2006) 811-814
19. Taylor P., Champness J., Given-Wilson R., Johnston K., and Potts H. Impact of computer-aided detection prompts on the sensitivity and specificity of screening mammography. Health Techn Assess 9 6 (2005) 1-58
20. Sahiner B., Chan H.P., Wei D., Petrick N., Helvie M.A., and Adler D.D. Image feature selection by a genetic algorithm: Application to classification of mass and normal breast tissue. Med Phys 23 (1996) 1671-1684
21. Qian W., Sun X., Song D., and Clark R.A. Digital mammography - wavelet transform and Kalman-filtering neural network in mass segmentation and detection. Acad Radiol 8 11 (2001) 1074-1082
22. Christoyianni I., Koutras A., Dermatas E., and Kokkinakis G. Computer aided of breast cancer in digitized mammograms. Comp Med Imag Grap 26 (2002) 309-319
23. Ojala T., Pietikainen M., and Maenpaa T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans Pattern Anal Machine Intell 24 7 (2002) 971-987
24. Oliver A., Lladó X., Freixenet J., and Martí J. False positive reduction in mammographic mass detection using local binary patterns. Int Conf Med Image Comput Comput Assist Interv 4478 (2007) 286-293
25. Zhang J., and Tan T. Brief review of invariant texture analysis methods. Pattern Recognit 35 3 (2002) 735-747
26. Ahonen T., Hadid A., and Pietikainen M. Face detection with local binary patterns: application to face recognition. IEEE Trans Pattern Anal Machine Intell 28 12 (2006) 2037-2041
27. Rangayyan R.M., Ayres F.J., and Desautels J.E.L. A review of computer-aided diagnosis of breast cancer: toward the detection of subtle signs. J Frankl Inst 344 3-4 (2007) 312-348
28. Suliga M., Deklerck R., and Nyssen E. Markov random field-based clustering applied to the segmentation of masses in digital mammograms. Comp Med Imag Grap 32 6 (2008) 502-512
29. Rojas A., and Nandi A. Detection of masses in mammograms via statistically based enhancement, multilevel-thresholding segmentation, and region selection. Comp Med Imag Grap 32 4 (2008) 304-315
30. Wu Y., Wei J., Hadjiiski L.M., Sahiner B., Zhou C., and Ge J. Bilateral analysis based false positive reduction for computer-aided mass detection. Med Phys 34 8 (2007) 3334-3344
31. van Engeland S., and Karssemeijer N. Combining two mammographic projections in a computer aided mass detection method. Med Phys 34 (2007) 898-905
32. Metz C.E. Evaluation of digital mammography by ROC analysis. Int Work Dig Mammogr (1996) 61-68
33. Angelini E., Campanini R., Iampieri E., Lanconelli N., Masotti M., and Roffilli M. Testing the performances of different image representations for mass classification in digital mammograms. Int J Mod Phys C 17 1 (2006) 113-131
34. Oliver A., Martí J., Martí R., Bosch A., and Freixenet J. A new approach to the classification of mammographic masses and normal breast tissue. IAPR Int Conf Pattern Recognit 4 (2006) 707-710
35. Turk M.A., and Pentland A.P. Eigenfaces for recognition. J Cognitive Neurosci 3 1 (1991) 71-86
36. Oliver A., Lladó X., Martí J., Martí R., and Freixenet J. False positive reduction in breast mass detection using two-dimensional PCA. Lect Not Comp Sci 4478 (2007) 154-161
37. Yang J., Zhang D., Frangi A.F., and Yang J. Two-dimensional PCA: a new approach to appearance-based face representation and recognition. IEEE Trans Pattern Anal Machine Intell 26 1 (2004) 131-137
38. Varela C., Tahoces P.G., Méndez A.J., Souto M., and Vidal J.J. Computerized detection of breast masses in digitized mammograms. Comput Biol Med 37 2 (2007) 214-226
39. Tourassi G.D., Eltonsy N.H., Graham J.H., Floyd C.E., and Elmaghraby A.S. Feature and knowledge based analysis for reduction of false positives in the computerized detection of masses in screening mammography. IEEE Conf Eng Med Biol Soc (2005) 6524-6527
40. Chang Y.H., Hardesty L.A., Hakim C.M., Chang T.S., Zheng B., and Good W.F. Knowledge-based computer-aided detection of masses on digitized mammograms: a preliminary assessment. Med Phys 28 4 (2001) 455-461
41. Tourassi G.D., Vargas-Vorecek R., Catarious D.M., and Floyd C.E. Computer-assisted detection of mammographic masses: A template matching scheme based on mutual information. Med Phys 30 8 (2003) 2123-2130
42. Tourassi G.D., Harrawood B., Singh S., Lo J.Y., and Floyd C.E. Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms. IEEE Trans Med Imag 34 1 (2007) 140-150
43. Ojala T., Pietikainen M., and Harwood D. A comparative-study of texture measures with classification based on feature distributions. Pattern Recognit 29 1 (1996) 51-59
44. Vapnik V. Statistical Learning Theory (1998), John Wiley & Sons, New York
45. Heath M., Bowyer K., Kopans D., Moore R., and Kegelmeyer P.J. The digital database for screening mammography. Int Work Dig Mammogr (2000) 212-218