Computer Assisted Diagnostic System in Tumor Radiography

@article{Faisal2013ComputerAD,
  title={Computer Assisted Diagnostic System in Tumor Radiography},
  author={Ahmed Faisal and Sharmin Parveen and Shahriar Badsha and Hasan Sarwar and Ahmed Wasif Reza},
  journal={Journal of Medical Systems},
  year={2013},
  volume={37},
  pages={1-10}
}
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… CONTINUE READING
BETA

Figures, Tables, Results, and Topics from this paper.

Key Quantitative Results

  • The obtained results also show detection accuracy of 99.46 %, which is a significant improvement than that of the existing results.

Citations

Publications citing this paper.
SHOWING 1-9 OF 9 CITATIONS

References

Publications referenced by this paper.
SHOWING 1-10 OF 28 REFERENCES

Noise removal using smoothed normals and surface fitting

  • IEEE Transactions on Image Processing
  • 2004
VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL

Digital Image Processing

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 1981
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Contrast enhancement technique based on local detection of edges

  • Computer Vision, Graphics, and Image Processing
  • 1989
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

An Improved Image Denoising and Segmentation Approach for Detecting Tumor from 2-D MRI Brain Images

  • 2012 International Conference on Advanced Computer Science Applications and Technologies (ACSAT)
  • 2012

Automatic brain tumor detection in Magnetic Resonance Images

  • 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)
  • 2012

A critical review of the effects of denoising algorithms on MRI brain tumor segmentation

I. Diaz, P. Boulanger, R. Griener, A Murtha
  • Annual International Conference of the IEEE EMBS,
  • 2011
VIEW 1 EXCERPT

Brain MRI segmentation for tumor detection using cohesion based self merging algorithm

  • 2011 IEEE 3rd International Conference on Communication Software and Networks
  • 2011
VIEW 1 EXCERPT

Segmentation and identification of brain tumor MRI image with Radix4 FFT techniques

R. Rajeswari, P. Anandhakumar
  • Eur. J. Sci. Res
  • 2011
VIEW 1 EXCERPT

Similar Papers