A Review : Brain tumor detection using Digital Image Processing

Authors

  • Dinesh M. Barode  Research Scholar, Department of Computer Science & Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India
  • Rupali S. Awhad  Research Scholar, Department of Computer Science & Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India
  • Seema S. Kawathekar  Assistant Professor, Department of Computer Science & Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India

DOI:

https://doi.org//10.32628/CSEIT2390154

Keywords:

DIP (Digital Image Processing), MRI (Magnetic resonance Image), Brain Tumor, classification, Segmentation, Feature Extraction, SVM (Support vector Machine)

Abstract

Now a day, one of the most common diseases is a brain tumor. The challenge is to identify a tumor at an early stage, which is essential to receiving good care and surviving brain cancer patients. In the human body, the uncontrolled growth of cells is called a brain tumor. They have different types and characteristics and have different treatments. Medical imaging techniques play an important role in the detection of brain tumors. Although MRI (Magnetic Resonance Imaging) is frequently regarded as the best method for identifying this type of tumor, it has several drawbacks, and MRI images are more sensitive to ambient noise and other disruptions. As a result, it is challenging for doctors to identify the tumor and its origin.

References

  1. Borole VY, Nimbhore SS, Kawthekar DS. Image processing techniques for brain tumor detection: A review. International Journal of Emerging Trends & Technology in Computer Science (IJETTCS). Volume4Issue5(2), 2015 Sep; 4(5):2. http://www.ijettcs.org/Volume4Issue5(2)/IJETTCS-2015-10-01-7.pdf
  2. Vipin Y. Borole, Seema S. Kawathekar, Study of various DIP Techniques used for Brain Tumor detection and tumor area calculation using MRI images, International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.39-43, 2016. https://www.ijcseonline.org/pdf_paper_view.php?paper_id=997&6-IJCSE-01741.pdf
  3. D. Moitra, R. Mandal , Review of Brain Tumor Detection using Pattern Recognition Techniques, International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.121-123, 2017. https://www.ijcseonline.org/pdf_paper_view.php?paper_id=1189&21-IJCSE-15-2017.pdf
  4. Vishal S. Shirsat, Seema S. Kawathekar, 2014, Classification of Brain Cancer Detection by using Magnetic Resonance Imaging, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) Volume 03, Issue 02 (February 2014), https://www.ijert.org/classification-of-brain-cancer-detection-by-using-magnetic-resonance-imaging#cite
  5. Takizawa D, Mizumoto M, Yamamoto T, Oshiro Y, Fukushima H, Fukushima T, Terunuma T, Okumura T, Tsuboi K, Sakurai H. A comparative study of dose distribution of PBT, 3D-CRT and IMRT for pediatric brain tumors. Radiation oncology. 2017 Dec; 12:1-7. https://link.springer.com/article/10.1186/s13014-017-0775-2
  6. Nithyasree C, Stanley D, Subalakshmi K, BRAIN TUMOR DETECTION USING IMAGE PROCESSING, International Journal on Cybernetics & Informatics (IJCI) Vol. 10, No.1/2, May 2021. https://ijcionline.com/paper/10/10221ijci35.pdf
  7. Bondy M, Wiencke J, Wrensch M, Kyritsis AP. Genetics of primary brain tumors: a review. Journal of neuro-oncology. 1994 Feb;18:69-81. https://link.springer.com/article/10.1007/BF01324606
  8. V.Vani, Probabilistic Neural Network design for Classification of Brain”, International Journal of Scientific Research in Computer Science Applications and Management Studies, ISSN 2319 – 1953Volume 8, Issue 1 (January 2019) https://www.ijsrcsams.com/images/stories/Past_Issue_Docs/ijsrcsamsv8i1p145.pdf 
  9. Priyanka BS. A review on brain tumor detection using segmentation. International Journal of Computer Science and Mobile Computing (IJCSMC). IJCSMC, Vol. 2, Issue. 7, July 2013, pg.48 – 54. https://ijcsmc.com/docs/papers/July2013/abstracts/V2I7201320.pdf
  10. Azzeddine Riahi, "Image Segmentation Techniques Based on Fuzzy C-Means and Otsu, Applied to the Brain MRI in Tumor Detection", International Journal of Computer Sciences and Engineering, Vol.3, Issue.12, pp.89-101, 2015. https://www.ijcseonline.org/pdf_paper_view.php?paper_id=762&14-IJCSE-01441.pdf 
  11. Akram MU, Usman A. Computer aided system for brain tumor detection and segmentation. International conference on Computer networks and information technology 2011 Jul 11 (pp. 299-302). IEEE. https://ieeexplore.ieee.org/abstract/document/6020885/
  12. Hiran KK, Doshi R. An artificial neural network approach for brain tumor detection using digital image segmentation. International Journal of Emerging Trends & Technology in Computer Science(IJETTCS), Volume 2, Issue 5, September – October 2013 https://www.researchgate.net/profile/KamalHiran/publication/320259291_An_Artificial_Neural_Network_Approach_for_Brain_Tumor_Detection_Using_Digital_Image_Segmentation/links/59d80df1a6fdcc2aad06540b/An-Artificial-Neural-Network-Approach-for-Brain-Tumor-Detection-Using-Digital-Image-Segmentation.pdf
  13. Wadhai SA, Kawathekar SS. Techniques of content based image retrieval: a review. IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727, PP 75-79, https://www.academia.edu/download/77145376/15._2075-79.pdf
  14. Kamble ST, Rathod MR. Brain tumor segmentation using K-means clustering algorithm. International Journal if Current Engineering and Technology. 2015 Jun; 5(3):1521-4.
  15. Sapra P, Singh R, Khurana S. Brain tumor detection using neural network. International Journal of Science and Modern Engineering (IJISME) ISSN. 2013 Aug: 23196386. https://www.ijisme.org/wpcontent/uploads/papers/v1i9/I0425081913.pdf
  16. Kumar S, Abid I, Garg S, Singh AK, Jain V. Brain Tumor Detection using Image Processing. International Journal of Information Sciences and Application (IJISA). ISSN09742255.2019;11(1). https://www.academia.edu/download/77141987/ijisav11n1spl_05.pdf
  17. Sravanthi N, Swetha N, Devi PR, Rachana S, Gothane S, Sateesh N. Brain tumor detection using image processing. Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol. 2021;7:348-52 https://www.researchgate.net/publication/352390016_Brain_Tumor_Detection_using_Image_Processing

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-04-30

Issue

Volume 9, Issue 2, March-April-2023

Section

Research Articles

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How to Cite

[1]
Dinesh M. Barode, Rupali S. Awhad, Seema S. Kawathekar, " A Review : Brain tumor detection using Digital Image Processing, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 2, pp.61-65, March-April-2023. Available at doi : https://doi.org/10.32628/CSEIT2390154