Abstract
Automated detection of masses on mammograms is challenged by the presence of dense breast parenchyma. The aim of this study is to investigate the feasibility of wavelet-based feature analysis in identifying spiculated and circumscribed masses in dense breast parenchyma. The method includes an edge detection step for breast border identification and employs Gaussian mixture modeling for dense parenchyma labeling. Subsequently, wavelet decomposition is performed and intensity as well as orientation features are extracted from approximation and detail subimages, respectively. Logistic regression analysis (LRA) is employed to differentiate spiculated and circumscribed masses from normal dense parenchyma. The proposed method is tested in 90 dense mammograms containing spiculated masses (30), circumscribed masses (30) and normal parenchyma (30). Free-response receiver operating characteristic (FROC) analysis is used to evaluate the performance of the method, achieving 83.3% sensitivity at 1.5 and 1.8 false positives per image for identifying spiculated and circumscribed masses, respectively.
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Chan, H.-P., Sahiner, B., Petrick, N., Hadjiiski, L., Paquerault, S.: Computer-Aided Diagnosis of Breast Cancer. In: Costaridou, L. (ed.) Medical Image Analysis Methods, pp. 1–49. CRC Press, Taylor & Francis Group, Boca Raton (2005)
Sampat, P.M., Markey, M.K., Bovik, A.C.: Computer-Aided Detection and Diagnosis in Mammography. In: Bovik, A.C. (ed.) Handbook of Image and Video Processing, 2nd edn., pp. 1195–1217. Academic Press, London (2005)
Kegelmeyer, J., Pruneda, J.M., Bourland, P.D., Hillis, A., Riggs, M.W., Nipper, M.L.: Computer-Aided Mammographic Screening for Spiculated Lesions. Radiology 191, 331–337 (1994)
Karssemeijer, N., te Brake, G.M.: Detection of Stellate Distortions in Mammograms. IEEE Trans. Med. Imag. 15, 611–619 (1996)
te Brake, G.M., Karssemeijer, N., Hendricks, J.H.C.L.: Automated Detection of Breast Carcinomas Not Detected in a Screening Program. Radiology 207, 465–471 (1998)
Wei, D., Chan, H.-P., Helvie, M.A., Sahiner, B., Petrick, N., Adler, D.D., Goodsitt, M.M.: Classification of Mass and Normal Breast Tissue on Digital Mammograms: Multiresolution Texture Analysis. Med. Phys. 22, 1501–1513 (1995)
Wei, D., Chan, H.-P., Petrick, N., Sahiner, B., Helvie, M.A., Adler, D.D., Goodsitt, M.M.: False-Positive Reduction Technique for Detection of Masses on Digital Mammograms: Global and Local Multiresolution Texture Analysis. Med. Phys. 24, 903–914 (1997)
Liu, S., Babbs, C.F., Delp, E.J.: Multiresolution Detection of Spiculated Lesions in Digital Mammograms. IEEE Trans. Image Proc. 10, 874–884 (2001)
Petrick, N., Chan, H.-P., Wei, D., Sahiner, B., Helvie, M.A., Adler, D.D.: Automated Detection of Breast Masses on Mammograms Using Adaptive Contrast Enhancement and Texture Classification. Med. Phys. 23, 1685–1696 (1996)
Kobatake, H., Murakami, M., Takeo, H., Nawano, S.: Computerized Detection of Malignant Tumors on Digital Mammograms. IEEE Trans. Med. Imag. 18, 369–378 (1999)
Zwiggelaar, R., Parr, T.C., Schumm, J.E., Hutt, I.W., Taylor, C.J., Astley, S.M., Boggis, C.R.M.: Model-based Detection of Spiculated Lesions in Mammograms. Med. Image Anal. 3, 39–62 (1999)
Chang, Y.-H., Hardesty, L.A., Hakim, C.M., Chang, T.S., Zheng, B., Good, W.F., Gur, D.: Knowledge-based Computer-Aided Detection of Masses on Digitized Mammograms: A Preliminary Assessment. Med. Phys. 28, 455–461 (2001)
Baydush, A.H., Catarious, D.M., Abbey, C.K., Floyd, C.E.: Computer Aided Detection of Masses in Mammography Using Subregion Hotteling Observers. Med. Phys. 30, 1781–1787 (2003)
Ho, W.T., Lam, P.W.T.: Clinical Performance of Computer-Assisted Detection (CAD) System in Detecting Carcinoma in Breast of Different Densities. Clin. Radiol. 58, 133–136 (2003)
Li, L., Zheng, Y., Zhang, L., Clark, A.: False-Positive Reduction in CAD Mass Detection Using a Competitive Classification Strategy. Med. Phys. 28, 250–258 (2001)
Tourassi, G.D., Vargas-Voracek, R., Catarious, D.M., Floyd, C.E.: Computer-Assisted Detection of Mammographic Masses: A Template Matching Scheme Based on Mutual Information. Med. Phys. 30, 2123–2130 (2003)
Aylward, S.R., Hemminger, B.M., Pisano, E.D.: Mixture Modeling for Digital Mammogram Display and Analysis. In: Karssemeijer, N., Thijssen, M., Hendriks, J., van Erning, A. (eds.) Digital Mammography Nijmegen, pp. 305–312. Kluwer Academic, Dordrecht (1998)
Sakellaropoulos, P., Costaridou, L., Panayiotakis, G.: A Wavelet-based Spatially Adaptive Method for Mammographic Contrast Enhancement. Phys. Med. Biol. 48, 787–803 (2003)
Costaridou, L., Sakellaropoulos, P., Skiadopoulos, S., Panayiotakis, G.: Locally Adaptive Wavelet Contrast Enhancement. In: Costaridou, L. (ed.) Medical Image Analysis Methods, pp. 225–270. Taylor & Francis Group LCC, CRC Press, Boca Raton (2005)
Costaridou, L., Sakellaropoulos, P., Stefanoyiannis, A., Ungureanu, E., Panayiotakis, G.: Quantifying Image Quality at Breast Periphery vs. Mammary Gland in Mammography Using Wavelet Analysis. Br. J. Radiol. 74, 913–919 (2001)
Yoshida, H., Doi, K., Nishikawa, R.M., Giger, M.L., Schmidt, R.A.: An Improved Computer-Assisted Diagnostic Scheme Using Wavelet Transform for Detecting Clustered Microcalcifications in Digital Mammograms. Acad. Radiol. 3, 621–627 (1996)
Chang, C.-M., Laine, A.: Coherence of Multiscale Features for Enhancement of Digital Mammograms. IEEE Trans. Med. Imag. 3, 32–46 (1999)
Mudigonda, N.R., Rangayyan, R.M., Desautels, L.J.E.: Detection of Breast Masses in Mammograms by Density Slicing and Texture Flow-Field Analysis. IEEE Trans. Med. Imag. 20, 1215–1227 (2001)
Sakellaropoulos, P., Costaridou, L., Panayiotakis, G.: An Image Visualization Tool in Mammography. Med. Inform. 24, 53–73 (1999)
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Sakellaropoulos, F., Skiadopoulos, S., Karahaliou, A., Costaridou, L., Panayiotakis, G. (2006). Using Wavelet-Based Features to Identify Masses in Dense Breast Parenchyma. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds) Digital Mammography. IWDM 2006. Lecture Notes in Computer Science, vol 4046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11783237_75
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DOI: https://doi.org/10.1007/11783237_75
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