Assessment of a breast mass identification procedure using an iris detector

IEEE Transactions on Instrumentation and Measurement

Volumn 59, Issue 10, 2010, Pages 2505-2512

  Mencattini, Arianna ^a   Rabottino, Giulia ^a   Salmeri, Marcello ^a   Lojacono, Roberto ^a  

^a UNIVERSITY OF ROME TOR VERGATA   (Italy)

Author keywords

Biomedical image processing; image identification; image processing; iris detector; metrological assessment

Indexed keywords

BIO-MEDICAL IMAGE PROCESSING; BREAST CANCER; BREAST MASS; EARLY DETECTION; GRADIENT VECTORS; IDENTIFICATION PROCEDURE; IMAGE IDENTIFICATION; IRIS DETECTOR; LOW CONTRAST; MAMMOGRAPHIC; METROLOGICAL ASSESSMENT; SCREENING PROGRAMS;

DETECTORS; DIAGNOSIS; IMAGE UNDERSTANDING;

IMAGING SYSTEMS;

EID: 77956766185     PISSN: 00189456     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIM.2010.2057691     Document Type: Article

References (26)

1. J. Ferlay, F. Bray, P. Psiani, and D.M. Parkin, Cancer Incidence,Mortality and Prevalence Worldwide IARC CancerBase no.5, Version 2.0. Lyon, France: IARCH Press, 2004.
2. L. J.W. Burhenne, S. A.Wood, and C. J. D'Orsi, "Potential contribution of computer aided detection to the sensitivity of screening mammography," Radiology, vol. 215, no. 2, pp. 554-562, May 2000.
3. M. Bazzocchi, F. Mazzarella, C. Del Frate, F. Girometti, and C. Zuiani, "CAD systems for mammography: A real opportunity? A review of the literature," La Radiologia Medica, vol. 112, no. 3, pp. 329-353, Oct. 2007.
4. M. Salmeri, A. Mencattini, G. Rabottino, A. Accattatis, and R. Lojacono, "Assisted breast cancer diagnosis environment: A tool for DICOM mammographic images analysis," in Proc. IEEE Int. Workshop Med. Meas. Appl., Cetraro, Italy, May 2009, pp. 160-165.
5. S. L. Liu, C. F. Babbs, and E. J. Delp, "Multiresolution detection of spiculated lesions in digital mammograms," IEEE Trans. Image Process., vol. 10, no. 6, pp. 874-884, Jun. 2001.
6. A. Lauria, "GPCALMA: Implementation in Italian hospitals of a computer aided detection system for breast lesions by mammography examination," Physica Medica, vol. 25, no. 2, pp. 58-72, Jun. 2009.
7. Y. Wang, H. Li, K. J. R. Liu, S.-C. B. Lo, and M. T. Freedman, "Computerized radiographic mass detection-Part I: Lesion site selection by morphological enhancement and contextual segmentation," IEEE Trans. Med. Imag., vol. 20, no. 4, pp. 289-301, Apr. 2001.
8. J. H. C. L. Hendriks, G. M. te Brake, and N. Karssemeijer, "An automatic method to discriminate malignant masses from normal tissue in digital mammograms,v Phys. Med. Biol., vol. 45, no. 10, pp. 2843-2857,Oct. 2000.
9. E. Iampieri, R. Campanini, D. Dongiovanni, N. Lanconelli, M. Masotti, G. Palermo, A. Riccardi, and M. Roffilli, "A novel featureless approach to mass detection in digital mammograms based on support vector machines," Phys. Med. Biol., vol. 49, no. 6, pp. 961-975, Mar. 2004.
10. C. E. Floyd, D. M. Catarious, and A. H. Baydush, "Incorporation of an iterative, linear segmentation routine into a mammographic mass CAD system," Med. Phys., vol. 31, no. 6, pp. 1512-1520, Jun. 2004.
11. H. Kobatake and M. Murakami, "Adaptive filter to detect rounded convex regions: Iris filter," in Proc. IEEE Int. Conf. Pattern Recog., 1996, vol. 2, pp. 340-344.
12. A. Mencattini, G. Rabottino, M. Salmeri, and R. Lojacono, "An iris detector for tumoral masses identification in mammograms," in Proc. IEEE Int. Workshop Med. Meas. Appl., Cetraro, Italy, May 2009, pp. 215-218.
13. University of South Florida, University of South Florida Digital Mammography Home Page, 2000. [Online]. Available: . csee.usf.edu/Mammography/ Database.html
14. American College of Radiology. [Online]. Available: www.acr.org
15. Breast Imaging Reporting and Data System. [Online]. Available: BIRADSAtlas.aspx
16. S. van Engeland, P. R. Snoeren, H. Huisman, C. Boetes, and N. Karssemeijer, "Volumetric breast density estimation from full-field digital mammograms," IEEE Trans. Med. Imag., vol. 25, no. 3, pp. 273-282, Mar. 2006.
17. A. Oliver, J. Freixenet, and R. Zwiggelaar, "Automatic classification of breast density," in Proc. IEEE Int. Conf. Image Process., 2005, vol. 2,pp. 1258-1261.
18. H. S. Sheshadri and A. Kandaswamy, "Breast tissue classification using statistical feature extraction of mammograms," Med. Imaging Inf. Sci., vol. 23, no. 3, pp. 105-107, 2006.
19. C. Balleyguier, S. Ayadi, K. Van Nguyen, D. Vanel, C. Dromain, and R. Sigal, "BIRADS classification in mammography," Eur. J. Radiol., vol. 61, no. 2, pp. 192-194, Feb. 2007.
20. A. Mencattini, M. Salmeri, R. Lojacono, and M. ArnÒ;, "Noise estimation in mammographic images for adaptive denoising," in Proc. EFOMP Eur. Conf. Med. Phys., Castelvecchio Pascoli, Italy, Sep. 2007.
21. S. Lankton and A. Tannenbaum, "Localizing region-based active contours," IEEE Trans. Image Process., vol. 17, no. 11, pp. 2029-2039,Nov. 2008.
22. R. Chandrasekhar, Y. Attikiouzel, S. M. Kwok, and M. T. Rickard, "Automatic pectoral muscle segmentation on mediolateral oblique view mammograms," IEEE Trans. Med. Imag., vol. 23, no. 9, pp. 1129-1140, Sep. 2004.
23. P. Jannin, E. Krupinski, and S. Warfield, "Validation in medical image processing," IEEE Trans. Med. Imag., vol. 25, no. 11, pp. 1405-1409,Nov. 2006.
24. M. Salmeri, A. Mencattini, G. Rabottino, and R. Lojacono, "Signaldependent noise characterization for mammographic images denoising," in Proc. IMEKO TC4 Symp., Firenze, Italy, Sep. 2008.
25. A. Mencattini, G. Rabottino, M. Salmeri, R. Lojacono, and E. Colini, "Breast mass segmentation in mammographic images by an effective region growing algorithm," in Advanced Concepts for Intelligent Vision Systems, vol. 5259, Lecture Notes in Computer Science. New York: Springer-Verlag, Oct. 2008, pp. 948-957.
26. A. Mencattini, M. Salmeri, R. Lojacono, G. Rabottino, and S. Romano, "Mammographic image analysis for tumoral mass automatic classification," in Proc. EFOMP Eur. Conf. Med. Phys., Castelvecchio Pascoli, Italy, Sep. 2007.