The Use of Diffusion Equations in the Detection Process of Suspicious Regions in Mammograms
Abstract
In this work we employ an anisotropic smoothing filter based on partial differential equations (PDE) as a preprocessing step for the detection of suspicious regions in mammograms. The filter to be used at the present work, preserves the region boundaries while smooths homogenous regions. The proposed method has been tested with a dataset of 56 images from the mini Mammographic Image Analysis Society (MIAS) database and 30 images selected from the Digital Database for Screening of Mammography (DDSM). The method is evaluated in terms of the number of true-positive detection and the rate average of false-positive per image with good results.References
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R. M. Rangayyan, F. J. Ayres, and J. E. Leo, Desautels. A review of computer-aided diagnosis of breast cancer: Toward the detection of subtle signs. Journal of The Franklin Institute, pp. 312–348, 2007.
M. L. Giger. Computer-aided diagnosis of breast lesions in medical images. IEEE Computer Society Press, pp. 39–45, Los Alamitos, CA, USA, 1995.
Z. Huo, M. L. Giger, C. J. Vyborny, D. E. Wolverton, and C. E. Metz. Computadorized classification of benign and malignant masses on digitized mammograms: A study of robustness. Academic Radiology, pp. 1077–1084. 2000.
Z. Huo, M. L. Giger, C. J. Vyborny, and C. E. Metz. Breast cancer: effectiveness of computer-aided diagnosis - observer study with independent database of mammograms. Academic Radiology, pp. 224–256. 2002.
S. Gupta, Chyn P.F., and M.K. Markey. Breast cancer cadx based on bi-rads descriptors from two mammographic views. Med. Phys, pp. 1810–1817. 2006.
E. D. C. Anderson, B. Muir, J. S. Walsh, and A. E. Kirkpatrick. The efficacy of double reading mammograms in breast screening. Clinical Radiology, pp. 248–251. 1994.
E. L. Thurfjell, K. A. Lernevall, and A. Taube. Benefit of independent double reading in a population-based mammography screening program. Radiological Society, pp. 241–244. 1994.
B. Verma and J. Zakos. A computer-aided diagnosis system for digital mammograms based on fuzzy-neural and feature extraction techniques. IEEE Trans. on Information Technology in Biomedicine, pp. 46–54, 2001.
J. A. Baker, E. L.Rosen, and J. Y. Lo. Computer-aided detection (cad) in screening mammography: Sensitivity of commercial cad systems for detection architectural distortion. American Journal of Roentgenology, pp. 1083–1088, 2003.
S. M. Astley and F. J. Gilbert. Computer-aided detection in mammography. Clinical Radiology, pp. 390–399. 2004.
N. Petrick, H. P. Chan, and B. Sahiner. An adaptive density-weighted contrast enhancement filter for mamographic breast mass detection. IEEE Trans. on Medical Imaging, pp. 59–67, 1996.
N. R. Mudigonda, R. M. Rangayyan, and J. E. Leo Desautels. Detection of breast masses in mammograms by density slicing and texture flow-field analysis. IEEE Trans. Med. Imaging, pp. 1215–1227, 2001.
W.E. Polakowski, D.A. Cournoyer, S.K. Rogers, M.P. Desimio, D.W. Ruck, J.W. Hoffmeister, and R.A. Raines. Computer-aided breast-cancer detection and diagnosis of masses using difference of gaussians and derivative-based feature saliency. IEEE Trans. on Medical Imaging, pp. 811–819, 1997.
N. Karssemeijer and J. H. C. L. Hendriks. Computer-assisted reading of mammograms. European Radiology, pp. 743–748. 1997.
A. Rojas Domínguez and A. K. Nandi. Detection of masses in mammograms using enhanced multilevel-thresholding segmentation and region selection based on rank. In BIEN ’07: Proceedings of the fifth IASTED International Conference, ACTA Press, pp. 370–375. 2007.
C. A. Z. Barcelos, M. Boaventura, and E. C. Silva Jr. A well-balanced flow equation for noise removal and edge detection. IEEE Trans. on Image Processing, pp. 751–763, 2003.
J. Parker J. Suckling and D. R. Dance. The mammographic image analysis society digital mammogram database. International Congress Series, pp. 375–378. 1994.
D. Kopans R. Moore M. Heath, K. Bowyer and P. Kegelmeyer Jr. The digital database for screening mammography. Digital Mammography, pp. 212–218. 2000.
American College of Radiology. Breast Imaging Reporting and Data System BI-RADS. American College of Radiology, Reston, VA, 4th edition, 2004.
P. Perona and J. Malik. Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Analysis and Machine Intelligence, pp. 629–639, 1990.
F. Catte, P. L. Lions, J. M. Morel, and T. Coll. Image selective smoothing and edge detection by nonlinear diffusion. SIAM J. Numer. Anal., pp. 182–193, 1992.
Published
2008-07-12
How to Cite
GULIATO, Denise; BARCELOS, Celia A. Zorzo; DIAS, Walter B..
The Use of Diffusion Equations in the Detection Process of Suspicious Regions in Mammograms. In: BRAZILIAN SYMPOSIUM ON COMPUTING APPLIED TO HEALTH (SBCAS), 8. , 2008, Belém/PA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2008
.
p. 121-130.
ISSN 2763-8952.
