Automated detection of masses in mammograms by local adaptive thresholding

Computers in Biology and Medicine

Volumn 37, Issue 1, 2007, Pages 37-48

  Kom, Guillaume ^a   Tiedeu, Alain ^a   Kom, Martin ^a  

^a Ecole National Superieure Polytechnique Cameroon   (Cameroon)

Author keywords

Adaptive thresholding; Computer aided detection; Mammogram; Mass; Segmentation

Indexed keywords

ADAPTIVE SYSTEMS; COMPUTER AIDED ANALYSIS; IMAGE ANALYSIS; IMAGE SEGMENTATION; RADIOLOGY;

ADAPTIVE THRESHOLDING; COMPUTER-AIDED DETECTION; RECEIVER OPERATING CHARACTERISTIC (ROC);

MAMMOGRAPHY;

ALGORITHM; ARTICLE; AUTOMATION; BREAST TUMOR; CONTROLLED STUDY; DATA BASE; HUMAN; IMAGE ANALYSIS; MAMMOGRAPHY; PRIORITY JOURNAL; RADIOLOGIST; RECEIVER OPERATING CHARACTERISTIC; ROC CURVE; SENSITIVITY ANALYSIS; TUMOR DIAGNOSIS;

ALGORITHMS; BREAST NEOPLASMS; DIAGNOSIS, COMPUTER-ASSISTED; FEMALE; HUMANS; MAMMOGRAPHY; RADIOGRAPHIC IMAGE ENHANCEMENT; SENSITIVITY AND SPECIFICITY;

EID: 33751006137     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2005.12.004     Document Type: Article

References (22)

1. A.G. Hauss, M.J. Yaffe, A categorical course in physics: technical aspects of breast imaging, in: 78th Scientific Assembly and Annual Meeting of RSNA (Radiological Society of North America), 1994.
2. van Dijck J.A.M., Verbeek L.M., Hendriks J.H.C.L., and Holland R. The current detectability of breast cancer in a mammographic screening program. Cancer 72 (1933) 1938-1993
3. Hutt I.W., Astley S.M., and Boggis C.R.M. Prompting as an aid to diagnosis in mammography. In: Gale A.G., Astley S.M., Dance D.R., and Cairns A.Y. (Eds). Digital Mammography (1994), Elsevier, Amsterdam 389-398
4. Clark R.A. Economic issues in screening mammography. Am. J. Radiol. 158 (1992) 527-534
5. Zuckerman H.C. The role of mammography in the diagnosis of breast cancer. In: Ariel I.M., and Clearly J.B. (Eds). Breast Cancer: Diagnosis and Treatment (1987), McGraw-Hill, New York 152-172
6. Pisano E.d., and Shtem F. Image processing and computer aided diagnosis in digital mammography: a clinical perspective. Int. J. Pattern Recog. Artific. Intell. 7 6 (1993) 1493-1503
7. Bassett L.W., Bunnell D.H., Gold R.H., Arndt R.D., and Linsman J. Breast cancer detection: one versus two views. Radiolgy 165 (1987) 95-97
8. Sickle E.A., Weber W.N., and Galvin H.B. Baseline screening mammography: one versus two views per breast. Am. J. Roentgenol. 147 (1986) 1149-1153
9. Wolerton D., Nishikawa R.M., Zouras W., and Doi K. CAD in digital mammography: computerized detection and classification of masses. In: Gale A.G., et al. (Ed). Digital Mammography (1994), Elsevier Science BV, Amsterdam
10. te Brake G.M., and Karssemeiger N. Detection of stellate breast abnormalities. In: Doi K., Giger M.L., Nishikawa R.M., and Schmidt R.A. (Eds). Digital Mammography 96 (1996), Elsevier, Amsterdam, The Netherlands 341-346
11. Petrick N., Chan H.P., Sahiner B., and Wei D. An adaptive density-weighted contrast enhancement filter for mammographic breast mass detection. IEEE Trans. Med. Imag. 15 1 (1996) 59-67
12. Kelgelmeyer W.P., Pruneda J.M., Bourland P.D., Hillis A., Riggs M.W., and Nipper M.L. Computer-aided mammographic screening for spiculated lesions. Radiology 191 (1994) 331-337
13. Kobatake H., Murakani M., Takéo H., and Nawano S. Computerized detection of malignant tumours on digital mammograms. IEEE Trans. Med. Imag. 18 5 (1999) 369-378
14. Li H., Wang Y., Ray Liu K.J., Shih-Chung B.L., and Freedman M.T. Computerized radiographic mass detection. Part I: lesion site selection by morphological enhancement and contextual segmentation. IEEE Trans. Image Process. 20 4 (2001) 289-300
15. Gupta R., and Undrill P.E. The use of texture analysis to identify suspicious masses in mammography. Phys. Med. Bio. 40 5 (1995) 835-855
16. Viton J.L., Rasigni M.R.G., and Llebaria A. Method for characterizing masses in digital mammograms. Opt. Eng. 35 12 (1996) 3453-3459
17. Li H., Wang Y., Ray Liu K.J., Shih-Chung B.L., and Freedman M.T. Computerized radiographic mass detection. Part II: decision support by featured database visualization and modular neural networks. IEEE. Trans. Med. Imag. 20 4 (2001) 302-313
18. K. Doi, Overview of state of the art and future requirements, in: Session 5B, Image processing and computer assisted diagnosis (CAD), Office of Women's Health (OWH) Workshop on Digital Mmmography, Washington, DC, 1-2 June, 1997.
19. Qian W., Li L., Clarke L., and Clark R.A. Digital mammography: comparison of adaptive and non-adaptive CAD methods for mass detection. Acad. Radiol. 6 8 (1999) 471-480
20. Li L., Qian W., and Clarke L.P. Image feature extraction for mass detection using digital mammography: effects of wavelet analysis. Proc. SPIE Med. Imag. 3338 (1998) 168-1176 Med. Phys. 26(3) (1999)
21. L. Li, W. Qian, L.P. Clarke, R.A. Clark, J. Thomas, Improving mass detection by adaptive and multi-scale processing in digitized mammograms, SPIE (Society of Photographic Scientists and Engineer) Conference on Image Processing, San Diego, CA, vol. 3661, February 1999, pp. 490-498.
22. Matsubara T., Fujita H., Hara T., Kasai S., Otsuka O., Hatanaka Y., and Endo T. Development of a new algorithm for detection of mammographic masses. Digital Mammogr. (Comput. Imag. Vision) 13 (1998) 139-142