Survey on Brain Tumor Identification

  • Authors

    • C Malathy
    • Namrata Kundu
    • Sayan Sadhukhan
    2018-07-20
    https://doi.org/10.14419/ijet.v7i3.12.16028
  • brain, tumor, identification, MRI
  • Abstract

    Brain tumors are caused by the growth of abnormal cells inside the Brain. Brain tumor can be classified as Benign (non cancerous) and malignant(cancerous). Malignant brain tumors usually grow rapidly when compared to benign tumors, and aggressively spread and affect the surrounding tissues. Detection of tumor in brain can turn out to be cumbersome, owing to the complex organization of the Brain. The cost of making an error in Identifying a Malignant Tumor from a Benign Tumor is too high. At a time, when cases of Brain Tumors are growing, mostly among people of age between 65 and 79, but not just confined to that age bracket, we can take advantage of the advancement in the field of technology and accurately identify tumors and help save lives.

     

     

     

  • References

    1. [1] Gauri P. Anandgaonkar, Ganesh.S.Sable, “Detection and Identification of Brain Tumor in Brain MR Images Using Fuzzy C-Means Segmentationâ€, International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 10, October 2013

      [2] Prof. A.S.Bhide, Priyanka Patil, Shraddha Dhande, “Brain Segmentation using Fuzzy C means clustering to detect tumour Regionâ€, ISSN: 2277 – 9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 2, April 2012

      [3] Nikita V. Chavan, B.D. Jadhav, P.M. Patil, “Detection and Classification of Brain Tumorsâ€,International Journal of Computer Applications (0975 – 8887) Volume 112 – No. 8, February 2015

      [4] CC Benson, VL Lajish, Kumar Rajamani, “Brain tumor extraction from MRI brain images using marker based watershed algorithmâ€, 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

      [5] Shweta Pandav, “Brain Tumor Extraction using Marker Controlled Watershed Segmentationâ€, International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 Vol.3 Issue 6, June-2014

      [6] Yogita Sharma, Parminder Kaur, “Detection and Extraction of Brain Tumor from MRI Images Using K-Means Clustering and Watershed Algorithmsâ€, International Journal of Computer Science Trends and Technology (IJCST) – Volume 3 Issue 2, Mar-Apr 2015

      [7] Sudipta Roy, Samir K. Bandyopadhyay, â€Detection and Quantification of Brain Tumor from MRI of Brain and it’s Symmetric Analysisâ€, International Journal of Information and Communication Technology Research Volume 2 No. 6, June 2012 ISSN 2223-4985

      [8] Benson C.C. and LajishV.L., â€Morphology Based Enhancement and Skull Stripping of MRI Brain Imagesâ€, 2014 International Conference on Intelligent Computing Applications

      [9] Meiyan Huang, Wei Yang, Yao Wu, Jun Jiang, Wufan Chen, Senior Member, IEEE, and Qianjin Feng*, Member, IEEE,†Brain Tumor Segmentation Based on Local Independent Projection- based Classificationâ€, DOI 10.1109/TBME.2014.2325410, IEEE Transactions on Biomedical Engineering

      [10] Janki Naik , Prof. Sagar Patel,â€Tumor Detection and Classification using Decision Tree in Brain MRIâ€, 2013 | IJEDR1301010 INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH | IJEDR

      [11] Zolt´an Kap´as ,L´aszl´o Lefkovits, L´aszl´o Szil´agyi,†Automatic Detection and Segmentation of Brain Tumor Using Random Forest Approachâ€, MDAI 2016: Modeling Decisions for Artificial Intelligence pp 301-312

      [12] Chinnu A,â€MRI Brain Tumor Classification Using SVM and Histogram Based Image Segmentationâ€, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 6 (2) , 2015, 1505-1508

      [13] Pydi Venkatesh, Srinivasa Babji Josyula,†Detection of Brain Tumor Using PCA with SVMâ€, International Journal of Research in Computer and Communication Technology, Vol 4, Issue 8, August -2015

      [14] Bhavana Ghotekar, Mrs. K. J. Mahajan,†Brain Tumor Detection and Classification using SVMâ€, NationalConference on Innovative Trends in Science and Engineering (NC-ITSE'16) Volume: 4 Issue: 7 ISSN: 2321-8169 180 - 182

      [15] SUSHMA V. TELRANDHE, DIVYA CHIKATE, POOJA BANODE,†AUTOMATED BRAIN TUMOR DETECTION USING BACKPROPAGATION NEURAL NETWORKâ€, International Journal of Soft Computing and Artificial Intelligence, ISSN: 2321-404X

      [16] https://healdove.com/disease-illness/What-is-a-Migraine-and-Why-May-Sumatriptan-Be-a-Good-Treatment

      [17] http://dxline.info/dictionary/brain-tumor#prettyPhoto

      [18] https://newsnetwork.mayoclinic.org/discussion/mayo-clinic-radio-lung-cancer-updatehousehold-health-hazardsprediabetes/

      [19] http://www.preventicum.co.uk/our-services/mri-scans-and-other-services/

      [20] http://drarunlnaik.com/neurodiagnostic_tests/

      [21] http://lovedriven.com/aura-byosen-scanning/

      [22] https://en.wikipedia.org/wiki/Magnetic_resonance_imaging

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  • How to Cite

    Malathy, C., Kundu, N., & Sadhukhan, S. (2018). Survey on Brain Tumor Identification. International Journal of Engineering & Technology, 7(3.12), 218-222. https://doi.org/10.14419/ijet.v7i3.12.16028

    Received date: 2018-07-22

    Accepted date: 2018-07-22

    Published date: 2018-07-20