Advertisement

Segmentation of Acute Brain Stroke from MRI of Brain Image Using Power Law Transformation with Accuracy Estimation

  • Sudipta Roy
  • Kingshuk Chatterjee
  • Samir Kumar Bandyopadhyay
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 27)

Abstract

Segmentation of acute brain stroke and its position is very important task in medical community. Accurate segmentation of brain’s abnormal region by computer aided design (CAD) system is very difficult and challenging task due to its irregular shape, size, high degree of intensity and textural similarity between normal areas and abnormal regions areas. We developed a new method using power law transformation which gives very fine result visually and from quantifiable point of view. Our methods gives very accurate segmented tumor output with very low error rate and very high accuracy.

Keywords

Brain Stroke MRI of Brain Power Law Transformation Segmentation Accuracy Estimation CAD system Abnormal Region 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Kosior, R.K., Lauzon, M.L., Steffenhagen, N., Kosior, J.C., Demchuk, A., Frayne, R.: Atlas-Based Topographical Scoring for Magnetic Resonance Imaging of Acute Stroke. American Heart Association 41(3), 455–460 (2010)Google Scholar
  2. 2.
    Kidwell, C.S., Chalela, J.A., Saver, J.L., Starkman, S., Hill, M.D., Demchuk, A.M., Butman, J.A., Patronas, N., Alger, J.R., Latour, L.L., Luby, M.L., Baird, A.E., Leary, M.C., Tremwel, M., Ovbiagele, B., Fredieu, A., Suzuki, S., Villablanca, J.P., Davis, S., Dunn, B., Todd, J.W., Ezzeddine, M.A., Haymore, J., Lynch, J.K., Davis, L., Warach, S.: Comparison of MRI and CT for Detection of Acute Intracerebral Hemorrhage. The Journal of the American Medical Association 292(15) (2004)Google Scholar
  3. 3.
    Chawla, M., Sharma, S., Sivaswamy, J., Kishore, L.: A method for automatic detection and classification of stroke from brain CT images. In: Proceedings of IEEE Engineering in Medicine and Biology Society, pp. 3581–3584 (2009)Google Scholar
  4. 4.
    Perez, N., Valdes, J., Guevara, M., Silva, A.: Spontaneous intracerebral hemorrhage image analysis methods: A survey. Advances in Computational Vision and Medical Image Processing Computational Methods in Applied Sciences 13, 235–251 (2009)CrossRefGoogle Scholar
  5. 5.
    Smith, E.E., Rosand, J., Greenberg, S.M.: Imaging of Hemorrhagic Stroke. Magnetic Resonance Imaging Clinics of North America 14(2), 127–140 (2006)CrossRefGoogle Scholar
  6. 6.
    Merino, J.G., Warach, S.: Imaging of acute stroke. Nature reviews. Neurology 6, 560–571 (2010)Google Scholar
  7. 7.
  8. 8.
    Roy, S., Nag, S., Maitra, I.K., Bandyopadhyay, S.K.: A Review on Automated Brain Tumor Detection and Segmentation from MRI of Brain. International Journal of Advanced Research in Computer Science and Software Engineerin 3(6), 1706–1746 (2013)Google Scholar
  9. 9.
    Roy, S., Dey, A., Chatterjee, K., Bandyopadhyay, S.K.: An Efficient Binarization Method for MRI of Brain Image. Signal & Image Processing: An International Journal (SIPIJ) 3(6), 35–51 (2012)Google Scholar
  10. 10.
    Barber, C.B., Dobkin, D.P., Huhdanpaa, H.: The Quickhull Algorithm for Convex Hulls. ACM Transactions on Mathematical Softwar 22(4), 469–483 (1996)CrossRefMATHMathSciNetGoogle Scholar
  11. 11.
    Daubechies, I.: Ten lectures on wavelets. CBMS-NSF conference series in applied mathematics. SIAM Ed. (1992)Google Scholar
  12. 12.
    Mallat, S.: A theory for multiresolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 11(7), 674–693 (1989)CrossRefMATHGoogle Scholar
  13. 13.
    Meyer, Y.: Ondelettesetopérateurs, Tome 1, Hermann Ed. (1990); English translation: Wavelets and operators. Cambridge Univ. Press (1993)Google Scholar
  14. 14.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. (2002)Google Scholar
  15. 15.
    Khotanlou, H.: 3D brain tumors and internal brain structures segmentation in MR images. Thesis (2008)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Sudipta Roy
    • 1
  • Kingshuk Chatterjee
    • 2
  • Samir Kumar Bandyopadhyay
    • 3
  1. 1.Department of Computer Science and EngineeringAcademy of TechnologyAdisaptagramIndia
  2. 2.E.C.S.U,Department of Computer Science and EngineeringIndian Statistical InstituteKolkataIndia
  3. 3.University of CalcuttaKolkataIndia

Personalised recommendations