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Articles
  • OpenAccess
  • A Novel Approach for Brain Tumor Detection Using MRI Images  [iCBBE 2016]
  • DOI: 10.4236/jbise.2016.910B006   PP.44 - 52
  • Author(s)
  • Abd El Kader Isselmou, Shuai Zhang, Guizhi Xu
  • ABSTRACT
  • Processing magnetic resonance images are very complex and constantly studied by the researchers to give doctors better ability to diagnose the patients. In order to detect automatically suspicious regions or tumors, we present a new approach inspired by threshold segmentation and based on morphological operations in this paper. The advantages of our approach come from the complementarities between these two approaches. The morphological operations extract roughly the tumor region and eventually can affect healthy while the threshold segmentation method gives a clear picture of the structure of the different brain and therefore these two approaches improve significantly the threshold segmentation and detection and extraction of the tumor zone based on morphological operations.
  • KEYWORDS
  • MRI, Threshold Segmentation, Morphological Operations, Tumor Identification, Filters
  • References
  • [1]
    Logeswari, T. and Karman, M. (2010) An Improved Implementation of Brain Tumor Detection Using Segmentation Based on Soft Computing. Journal of Cancer Research and Experimental Oncology, 2, 6-14.
    [2]
    American Brain Tumor Association (2012) Facts and Statistics, 2012.
    http://www.abta.org/secure/about-brain-tumors-a-primer.pdf
    [3]
    National Cancer Institute Dictionary of Cancer Terms.
    http://www.cancer.gov/publications/dictionaries/cancer-terms
    [4]
    Devos, A. and Lukas, L. (2014) Does the Combination of Magnetic Re-sonance Imaging and Spectroscopic Imaging Improve the Classification of Brain Tumors? IEMBS’ 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1-5 September 2004, 407 410.
    [5]
    Natarajan, P., Krishnan, N., Kenkre, N.S., Nancy, S. and Singh, B.P. (2012) Tumor Detection Using Threshold Operation in MRI Images. IEEE 2012.
    [6]
    Gajanayak, G.M.N.R., Yapal, R.D. and Hewawithana, B. (2009) Comparison of Standard Image Segmentation Methods of Brain Tumors from 2D MR Images. ICIIS 2009, 28-31 December 2009.
    http://dx.doi.org/10.1109/iciinfs.2009.5429848
    [7]
    Resmi, A.S. and Thomas, T. (2012) Automatic Segmentation Framework for Primary Tumors from Brain MRIs Using Morphological Filtering Techniques. 5th BMEI, 2012.
    [8]
    Thapaliya, K. and Kwon, G.R. (2012) Extraction of Brain Tumor Based on Morphological Operations. 8th (ICCM) 2012.
    [9]
    Ahmed, F., Sharmin, P., Shahriar, B. and Sarwar, S. (2012) An Improved Image Denoising and Segmentation Approach for Detecting Tumor from 2-D MR Brain Images. IEEE 2012.

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