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Tumor Detection in Brain Magnetic Resonance Images Using Modified Thresholding Techniques

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Advances in Computing and Communications (ACC 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 193))

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Abstract

Automated computerized image segmentation is very important for clinical research and diagnosis. The paper deals with two segmentation schemes namely Modified Fuzzy thresholding and Modified minimum error thresholding. The method includes the extraction of tumor along with suspected tumorized region which is followed by the morphological operation to remove the unwanted tissues. The performance measure of various segmentation schemes are comparatively analyzed based on segmentation efficiency and correspondence ratio. The automated method for segmentation of brain tumor tissue provides comparable accuracy to those of manual segmentation.

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Author information

Authors and Affiliations

  1. ECE Dept, Rajagiri School of Engineering & Technology, Kochi, India

    C. L. Biji & Asha Panicker

  2. ECE Dept, Mepco Schlenk Engineering College, Sivakasi, India

    D. Selvathi

Authors
  1. C. L. Biji
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  2. D. Selvathi
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  3. Asha Panicker
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Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs (MIR Labs), Auburn, 98071-2259, Washington, USA

    Ajith Abraham

  2. Departamento de Comunicaciones, Universidad Politcnica de Valencia, 46071, Valencia, Spain

    Jaime Lloret Mauri

  3. Avaya Labs Research, Basking Ridge, NJ, USA

    John F. Buford

  4. University of Massachusetts, 100 Morrissey Blvd., 02125-3393, Boston, MA, USA

    Junichi Suzuki

  5. Rajagiri School of Engineering and Technology, Rajagiri Valley Kakkanad, 682 039, Kochi, India

    Sabu M. Thampi

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© 2011 Springer-Verlag Berlin Heidelberg

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Biji, C.L., Selvathi, D., Panicker, A. (2011). Tumor Detection in Brain Magnetic Resonance Images Using Modified Thresholding Techniques. In: Abraham, A., Mauri, J.L., Buford, J.F., Suzuki, J., Thampi, S.M. (eds) Advances in Computing and Communications. ACC 2011. Communications in Computer and Information Science, vol 193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22726-4_32

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  • DOI: https://doi.org/10.1007/978-3-642-22726-4_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22725-7

  • Online ISBN: 978-3-642-22726-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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