Abstract
Digital images are a convenient media for describing and storing spatial, temporal, spectral, and physical components of information contained in a variety of domains (e.g. aerial/satellite images in remote sensing, medical images, etc.). In the paper we address the problem of efficiently and accurately retrieving images from a medical database purely based on shape analysis. The detection of mass lesions on mammograms can be a difficult task for human observers or machines. The potential variability and heterogeneity of normal breast tissue often produces a number of localized findings that may simulate mass lesions or, depending on the observer, create distractions, during the search process. The tool we’ll test in this paper represents contours and textures by a vector containing the location and the energy of the signal maxima. The main contribute of this work shows how the method works as information retrieval from image dataset and also as Cad system.
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References
Tabar, L., Fagerberg, G., Duffy, S.W. et al: Update in the Swedish two-country program of mammografic screening for breast cancer. Radiol. Clin. North Am. (1992) 30: 187–210
Smart, CR., Byrnes, C., Smith, R.A. et al: Twenty-years follow-up of the breast cancers dignosed during the breast cancer detection demonstration project. Ca Cancer I. Clin. (1997) 47:135–149
MacMahon, H., Doi, K. et al: Computer-aided-diagnosis in chest radiology. J. Thoracic Imaging, (1990) 5:67–76
Doi, K., Giger ML et al: A useful clinical tool for CAD diagnosis by quantitative analysis of radiografic images. Acta radiology (1993) 34:426-39
Rosen, M.P., Levine, D. et al: Diagnostic accuracy with US: remote radiologists versus On-site radiologists interpretation. Radiology (1999) 210:733–736
Vyborny, C.J., Tekeshi Doi et al: Breast cancer: importance of spiculation in CAD. Radiology (2000) 215:703–707
Distasi, R., Vitulano, S. et al: Context: A Technique for image retrieval Integrating Contour and Texture Information. To appear in Prooc. ICIAP01, (2001)
Distasi, R., Vitulano, S. et al: A Hierarchical Representation for Content-based Image Retrieval. Journal of Visual Language and Computing (2000) 11:369–382
Zheng, B., Chang, H.Y. et al: Mass detection in digitized mammograms using two indipendent CAD schemes. AJR (1996) 167:1421-24
Chan, H.P. et al: CAD of mammografic microcalcification: pattern recognition with an artificial neural network. Med. Phys (1995) 22:1555-67
Wei, D. et al: Classification Of mass and normal breast tissue on digital mammograms: multiresolution texture analysis. Med.Phys (1995) 22:1501-13
Zheng, B. et al: Computirized detection of masses in digitized mammograms using single-image segmentation and a multilayer topographic feature analysis. Acad. Radiol. (1995) 2:959-66
Chang, Y.H. et al: Computerized identification of suspicious regions for masses in digitized mammograms. Invest. Radiol. (1996) 31:143-50
Davies, D.H. et al: Automatic computer decision of clustered microcalcification in digital mammograms. Physics in Medicine and Biology (1999) 35:1111-18
Dengler, J. et al: Segmentation of microcalcification in mammograms. IEEE Tran. On Medical Imaging (1993) 12:634-44
Shen, L. et al: Application of shape analysis to mammographic calcifications. IEEE Trans. On Medical Imaging (1993) 13:263-74
Karsseme, I.J. et al: Adaptive noise equalization and recognition of microcalcification cluster in mammograms. Int. Journal of Pattern Recognition and Artificial Intell. (1993) 7:263-74
Dinten, J.M. et al: A global approach for localization and characterization of microcalcification in mammograms. Digital mammography (1996) Elsevier:235-38
Chitre, Y. et al: Adaptive wavelet analysis and classification of mammographic calcification. Digital mammography (1996) Elsevier:323-26
Strckland, R.N. et al: Wavelet transform for detecting microcalcification in mammograms IEEE Trans. On Medical imaging (1996) 218-29
Wang, T.C. et al: Detection of microcalcification in digital mammograms using wavelet. IEEE Trans. On Medical Imaging (1998) 498–509
Vitulano, S. et al: Different methods to segment biomedical images. Pattern Recognition Letters (1997) 18:1125-31
Vitulano, S. et al: edge detection: local and global operators. International Journal of Pattern recognition and Artificial Intelligence (1998) 12:677-93
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Balestrieri, A., Balestrieri, A., Barone, A., Casanova, A., Fraschini, M. (2001). Information Retrieval from Medical Database. In: Tucci, M. (eds) Multimedia Databases and Image Communication. MDIC 2001. Lecture Notes in Computer Science, vol 2184. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44819-5_4
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DOI: https://doi.org/10.1007/3-540-44819-5_4
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