Assessment of a novel mass detection algorithm in mammograms

Journal of Cancer Research and Therapeutics

Volumn 9, Issue 4, 2013, Pages 592-600

  Kozegar, Ehsan ^a   Soryani, Mohsen ^a   Minaei, Behrouz ^a   Domingues, Inês ^b  

^a IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

^b UNIVERSITY OF PORTO   (Portugal)

Author keywords

Classification; detection; FROC analysis; mammograms; masses

Indexed keywords

ALGORITHM; BREAST; BREAST NEOPLASMS; COMPUTER ASSISTED DIAGNOSIS; EARLY DIAGNOSIS; FEMALE; HUMAN; IMAGE QUALITY; MAMMOGRAPHY; MASS SCREENING; PROCEDURES; RADIOGRAPHY;

ALGORITHMS; BREAST; BREAST NEOPLASMS; DIAGNOSIS, COMPUTER-ASSISTED; EARLY DETECTION OF CANCER; FEMALE; HUMANS; MAMMOGRAPHY; MASS SCREENING; RADIOGRAPHIC IMAGE ENHANCEMENT;

EID: 84894481068     PISSN: 09731482     EISSN: 19984138     Source Type: Journal    
DOI: 10.4103/0973-1482.126453     Document Type: Article

References (24)

1. De Oliviera J, De Albuquerque A, Deserno TM. Content-based image retrieval applied to BI-RADS tissue classification in screening mammography. World J Radiol 2011;3:24-31.
2. Oliveira ML, Braz JG, Cardoso P, Gattass M. Detection of masses in digital mammograms using K-means and support vector machine. ELCVIA 2009;8:39-50.
3. Malagelada AO. Automatic mass segmentation in mammographic images, Ph.D. dissertation, Department of Electronics-Computer Science and Automatic Control. University of Girona, Spain; 2007.
4. Petrick N, Chan HP, Sahiner B, Wei D. An adaptive density-weighted contrast enhancement filter for mammographic breast mass detection. IEEE Trans Med Imaging 1996;15:59-67.
5. Kobatake H, Murakami M, Takeo H, Nawan S. Computerized detection of malignant tumors on digital mammograms. IEEE Trans Med Imaging 1999;18:369-78.
6. Varela C, Tahoces PG, Mendez AJ, Souto M, Vidal JJ. Computerized detection of breast masses in digitized mammograms. Comput Biol Med 2007;37:214-26.
7. Kom G, Tiedeu A, Kom M. Automated detection of masses in mammograms by local adaptive thresholding. Comput Biol Med 2007;37:37-48.
8. Fauci F, Raso G, Magro R, Forni G, Lauria A, Bagnasco S, et al. A massive lesion detection algorithm in mammography. Phys Med 2005;21:23-30.
9. Eltonsy NH, Tourassi GD, Elmaghraby AS. A concentric morphology model for the detection of masses in mammography. IEEE Trans Med Imaging 2007;26:880-9.
10. Martins LD, Paiva AC, Gattass M. Detection of breast masses in mammogram images using growing neural gas algorithm and ripleys k function. J Signal Process Syst 2009;55:77-90.
11. Nguyen VD, Nguyen DT, Nguyen TD, Thi N, Tran DH. A program for locating possible breast masses on mammograms. In: Proceeding of the 3rd International Conference on the Development of BME, Springer, Vietnam, 2010. p. 11-4.
12. Lochanambal KP, Karnan N, Sivakumar R. Identifying masses in mammograms using template matching. In: Second International Conference on Communication Software and Networks, IEEE, Singapore 2010.
13. Lai SM, Li X, Bischof WF. On techniques for detecting circumscribed masses in mammograms. IEEE Trans Med Imaging 1989;8:377-86.
14. Mencattini A, Salmeri M. Breast masses detection using phase portrait analysis and fuzzy inference systems. IJCARS 2011;7:573-83.
15. Singh WJ, Nagarajan B. Automatic diagnosis of mammographic abnormalities based on hybrid features with learning classifier. Comput Methods Biomech Biomed Engin 2012.
16. Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP. SMOTE: Synthetic minority over-sampling technique. J Artif Intell Res 2002;16:321-57.
17. Masotti M, Campanini R. Texture classification using invariant ranklet features. Pattern Recognit Lett 2008;29:1980-6.
18. Yang SC, Wang CM, Chung YN, Hsu GC, Lee SK, Chung PC, et al. A computer-aided system for mass detection and classification in digitized mammograms. Biomed Eng-App Bas C 2005;17:215-28.
19. Haralick RM, Shanmugan K, Dinstein I. Textural features for image classification. IEEE Trans Syst Man Cybern 1973;3:610-21.
20. Xu R, Zhao X, Li X, Kwan C, Chang C. Target detection with improved image texture feature coding method and support vector machine. IJIT 2006;1:47-56.
21. Suckling J. The mammographic image analysis society digital mammogram database. In: Exerpta Medica International Congress Series, Elsevier, New York 1994;1069. p. 375-8.
22. Moreira IC, Amaral I, Domingues I, Cardoso A, Cardoso MJ, Cardoso JS. INbreast: Towards a full field digital mammographic database. Acad Radiol 2012;19:236-48.
23. Oliver A, Freixenet J, Martí J, Pérez E, Pont J, Denton ER, et al. A review of automatic mass detection and segmentation in mammographic images. Med Image Anal 2010;14:87-110.
24. Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH. The WEKA Data Mining Software. SIGKDD Explorations 2009;11:10-8.