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Computer Assisted Diagnostic System in Tumor Radiography

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Abstract

An improved and efficient method is presented in this paper to achieve a better trade-off between noise removal and edge preservation, thereby detecting the tumor region of MRI brain images automatically. Compass operator has been used in the fourth order Partial Differential Equation (PDE) based denoising technique to preserve the anatomically significant information at the edges. A new morphological technique is also introduced for stripping skull region from the brain images, which consequently leading to the process of detecting tumor accurately. Finally, automatic seeded region growing segmentation based on an improved single seed point selection algorithm is applied to detect the tumor. The method is tested on publicly available MRI brain images and it gives an average PSNR (Peak Signal to Noise Ratio) of 36.49. The obtained results also show detection accuracy of 99.46 %, which is a significant improvement than that of the existing results.

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Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Department of Computer System & Technology, Faculty of Computer Science & Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Ahmed Faisal & Sharmin Parveen

  2. Faculty of Engineering, Department of Electrical Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Shahriar Badsha & Ahmed Wasif Reza

  3. Department of Computer Science and Engineering, United International University, Dhaka, Bangladesh

    Hasan Sarwar

Authors
  1. Ahmed Faisal
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  2. Sharmin Parveen
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  3. Shahriar Badsha
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  4. Hasan Sarwar
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  5. Ahmed Wasif Reza
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Correspondence to Ahmed Wasif Reza.

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Faisal, A., Parveen, S., Badsha, S. et al. Computer Assisted Diagnostic System in Tumor Radiography. J Med Syst 37, 9938 (2013). https://doi.org/10.1007/s10916-013-9938-3

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  • DOI: https://doi.org/10.1007/s10916-013-9938-3

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