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Design Objectives and Methodology for Computer-aided Analysis of Mammograms

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Non-Linear Filters for Mammogram Enhancement

Part of the book series: Studies in Computational Intelligence ((SCI,volume 861))

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Abstract

The aim of the research work presented in this book is to provide a reliable CAD solution for breast cancer performing enhancement for automated analysis of mammograms.

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References

  • A.J. Evans, A.R.M. Wilson, H.C. Burrell, I.O. Ellis, S.E. Pinder, Mammographic features of ductal carcinoma in situ present on previous mammography. Clin. Radiol. 54(10), 644–646 (1999)

    Google Scholar 

  • M. Jourlin, J.C. Pinoli, Logarithmic image processing: the mathematical and physical framework for the representation and processing of transmitted images. Adv. Imaging Electron Phys. 115, 129–196 (2001)

    Google Scholar 

  • M.K. Kundu, S.K. Pal, Thresholding for edge detection using human psychovisual phenomena. Pattern Recognit. Lett. 4(6), 433–441 (1986)

    Article  Google Scholar 

  • W.M. Morrow, R.B. Paranjape, R.M. Rangayyan, J.E.L. Desautels, Region-based contrast enhancement of mammograms. IEEE Trans. Med. Imaging 11(3), 392–406 (1992)

    Article  Google Scholar 

  • L. Navarro, G. Deng, G. Courbebaisse, The symmetric logarithmic image processing model. Digit. Signal Process. 23(5), 1337–1343 (2013)

    Article  MathSciNet  Google Scholar 

  • K.A. Panetta, Z. Yicong, S.S. Agaian, H. Jia, Non-linear unsharp masking for mammogram enhancement. IEEE Trans. Inf. Technol. Biomed. 15(6), 918–928 (2011)

    Article  Google Scholar 

  • S. Singh, R. Al-Mansoori, Identification of regions of interest in digital mammograms. J. Intell. Syst. 10(2), 183–217 (2000)

    Google Scholar 

  • S. Singh, K. Bovis, An evaluation of contrast enhancement techniques for mammographic breast masses. IEEE Trans. Inf. Technol. Biomed. 9(1), 109–119 (2005)

    Article  Google Scholar 

  • E. Wharton, S. Agaian, K. Panetta, A logarithmic measure of image enhancement, in Mobile Multimedia/Image Processing for Military and Security Applications, SPIE 6250, May 2006, pp. 1–15

    Google Scholar 

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Correspondence to Vikrant Bhateja .

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Bhateja, V., Misra, M., Urooj, S. (2020). Design Objectives and Methodology for Computer-aided Analysis of Mammograms. In: Non-Linear Filters for Mammogram Enhancement. Studies in Computational Intelligence, vol 861. Springer, Singapore. https://doi.org/10.1007/978-981-15-0442-6_12

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