Detection and feature extraction of CT lung tumor using cad system

  • Authors

    • A Josephin Arockia Dhivya
    • R J. Hemalatha
    • T R. Thamizhvani
    • Josline Elsa Joseph
    • Bincy Babu
    • R Chandrasekaran
    2018-05-03
    https://doi.org/10.14419/ijet.v7i2.25.16568
  • Lung, Feature Extraction, Detection, Pulmonary Embolism.

  • Abstract

    A 64 slice computed tomography is used for treating pulmonary related embolism diseases.Pulmonary embolism is a condition which causes death for all age group people.In a decade analyzing, computed tomography technique is regarded as the minimally painful technique.In this condition basically there are five steps involved in it.The first step involved is segmenting the lung sec-tion.The second step briefly delivers about PE extraction using a mask of high intensity.The third step involves in extracting the features in the image.The fourth step is reducing the features using artificial neural networks.The fifth step involves a multi fea-ture system having k as its neighbor,which is helpful for classifying positive and negative differentiation.There are few other methods to improve the performance.:They use tobogganing algorithm and they use the method of grouping and it attained the sensitivity of 80%Other scoring methods are achieved and performance has been enhanced.It also improves CAD performance.

     

     

     

  • References

    1. [1] H. P. Chan, L. Hadjiiski, C. Zhou, and B. Sahiner, “Computer-aided diagnosis of lung cancer and pulmonary embolism in computed tomography— A review,†Acad. Radiol., vol. 15, pp. 535–555, 2008.

      [2] J, Brink and et al., Helical CT: Principles and Technical Considerations. RadioGraphics, 1994, 14(4), p. 887 - 893.

      [3] Bland, P.H. and C.R. Meyer, Roboust threedimensional object definition in CT and MRI. Med. Phys., 1996, 23(1), p. 99-107

      [4] M. Das, G. M¨uhlenbruch, A. Helm, A. Bakai, M. Salganicoff, S. Stanzel, J. Liang, M.Wolf, R.W. G¨unther, and J. E.Wildberger, “Computer-aided detection of pulmonary embolism: Influence on radiologists’ detection performance with respect to vessel segments,†Eur. Radiol., vol. 18, pp. 1350–1355, 2008

      [5] J. Liang and J. Bi, “Computer aided detection of pulmonary embolism with tobogganing in CT angiography,†in Proc. ICIP Medical Imag., 2007, pp. 630–641.

      [6] Hemalatha.R J, V. Vijayabaskar, Josline Elsa Joseph, Harikrishnan. G, S. Krishnakumar;Medical Image Segmentation Algorithms For Ultrasound Images,Biomedicine, 2017.vol 37(1),pp. 2-7.

      [7] S. Buhmann, P. Herzog, J. Liang, M. Wolf, M. Salganicoff, C. Kirchhoff, M. Reiser, and C. H. Becker, “Clinical evaluation of a computer-aided diagnosis (CAD) prototype for the detection of pulmonary embolism,†Acad. Radiol., vol. 14, pp. 651–658, 2007

      [8] Wang, G. and M.W. Vannier, Longitudinal resolution in volumetric x-ray computerized tomography - Analytical comparison between conventional and helical computerized tomography. Med. Phys., 1994, 21(3), p. 429 - 433.

      [9] Y. Masutani, H. MacMahon, and K. Doi, “Computerized detection of pulmonary embolism in spiral CT angiography based on volumetric image analysis,†IEEE Trans. Med. Imag., vol. 21, no. 12, pp. 1517–1523, Dec. 2002.

      [10] U. J. Schoepf, A. C. Schneider, M. Das, S. A. Wood, J. I. Cheema, and P. Costello, “Pulmonary embolism: Computer-aided detection at multidetector row spiral computed tomography,†J. Thorac. Image. vol. 22, pp. 319–323, 2007.

      [11] Hemalatha R.J., Vijayabaskar V. Despeckling Filter Evaluation Using Image Quality Metrics and Coefficient of Variation. In: Bhattacharyya P., Sastry H., Marriboyina V., Sharma R. (eds) Smart and Innovative Trends in Next Generation Computing Technologies. NGCT 2017. Communications in Computer and Information Science, Springer, 2018, Jun 828(65).

      [12] Hemalatha.R.J, G.Harikrishnan, G.Umashankar, Sheeba Abrahampublished a paper on “Computerized Breast Cancer Detection System†inBiosciences, Biotechnology Research Asia, Vol. 11 No. 02, August 2014.

      [13] Z. V. Maizlin, P. M. Vos, M. C. Godoy, and P. L. Cooperberg, “Computeraided detection of pulmonary embolism on CT angiography: Initial experience,†J. Thorac. Imag. vol. 22, pp. 324–329, 2007.

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  • How to Cite

    Josephin Arockia Dhivya, A., J. Hemalatha, R., R. Thamizhvani, T., Elsa Joseph, J., Babu, B., & Chandrasekaran, R. (2018). Detection and feature extraction of CT lung tumor using cad system. International Journal of Engineering & Technology, 7(3), 100-104. https://doi.org/10.14419/ijet.v7i2.25.16568

    Received date: 2018-07-30

    Accepted date: 2018-07-30

    Published date: 2018-05-03