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Medical Image Analysis using Machine Learning Techniques

Shubham Kumar Raj1 , Nitesh Kumar2 , Gopal Mani Dubey3 , Rajshekhar S A4

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-15 , Page no. 159-163, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si15.159163

Online published on May 16, 2019

Copyright © Shubham Kumar Raj, Nitesh Kumar, Gopal Mani Dubey, Rajshekhar S A . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Shubham Kumar Raj, Nitesh Kumar, Gopal Mani Dubey, Rajshekhar S A, “Medical Image Analysis using Machine Learning Techniques,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.15, pp.159-163, 2019.

MLA Style Citation: Shubham Kumar Raj, Nitesh Kumar, Gopal Mani Dubey, Rajshekhar S A "Medical Image Analysis using Machine Learning Techniques." International Journal of Computer Sciences and Engineering 07.15 (2019): 159-163.

APA Style Citation: Shubham Kumar Raj, Nitesh Kumar, Gopal Mani Dubey, Rajshekhar S A, (2019). Medical Image Analysis using Machine Learning Techniques. International Journal of Computer Sciences and Engineering, 07(15), 159-163.

BibTex Style Citation:
@article{Raj_2019,
author = {Shubham Kumar Raj, Nitesh Kumar, Gopal Mani Dubey, Rajshekhar S A},
title = {Medical Image Analysis using Machine Learning Techniques},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {07},
Issue = {15},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {159-163},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1219},
doi = {https://doi.org/10.26438/ijcse/v7i15.159163}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i15.159163}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1219
TI - Medical Image Analysis using Machine Learning Techniques
T2 - International Journal of Computer Sciences and Engineering
AU - Shubham Kumar Raj, Nitesh Kumar, Gopal Mani Dubey, Rajshekhar S A
PY - 2019
DA - 2019/05/16
PB - IJCSE, Indore, INDIA
SP - 159-163
IS - 15
VL - 07
SN - 2347-2693
ER -

           

Abstract

Image Processing has been a growing field for the biomedical images. MRI, CT scans and X-Ray are the different types ofimages used in this technique. All these techniques helps to identify even a minute deformity in the human body. The main purpose of medical image processing is to extract meaningful information from these images. MRI is the most reliable form of biomedical image available to us asit does not expose the human body to any sorts of harmful radiation. Once the MRI is obtained it can be processed, and the part of brain affected by tumor can be segmented. The complete process of detecting brain tumor from an MRI can be classified into four different categories: Pre-Processing, Segmentation,Feature Extraction and Tumor Detection. This survey involves analyzing and taking help of the research by other professionals and compiling it into one paper.

Key-Words / Index Term

OpenCV, Image Processing, Active contour, Machine Learning, Segmentation, Feature Extraction

References

[1] Justin Ker, Lipo Wang, Jai Raoi and Tchoyoson Lim, “Deep Learning Applications in Medical Image Analysis” IEEE Trans.Med. Imag., vol. 35, no. 5, pp. 13221331, December 29, 2017.
[2] Z. Akkus, A. Galimzianova, A. Hoogi, D. L. Rubin, and B. J. Erickson, ``Deep learning for brain MRI segmentation: State of the art and future directions,`` J. Digit. Imag., vol. 30, no. 4, pp. 449459, 2017.
[3] Natarajan P, Krishnan.N, Natasha Sandeep, Kenkre,Shraiya Nancy, Bhuvanesh Pratap Singh, "Tumor Detection using threshold operation in MRI Brain Images", IEEE International Conference on Computational Intelligence and Computing Research, 2012.
[4] M. Havaei et al., ``Brain tumor segmentation with deep neural networks,``Med. Image Anal., vol. 35, pp. 18_31, Jan. 2017.
[5] M. Alfonse and A.-B. M. Salem, “An automatic classification of brain tumors through MRI using support vector machine,” Egyptian Computer Science Journal, vol. 40, pp. 11–21, 2016.
[6] Komal Sharma, Akwinder Kaur, Shruti Gujral, “Brain Tumor Detection based on Machine Learning Algorithms”, International Journal of Computer Applications (0975 – 8887) Volume 103 – No.1, October 2014.
[7] S. Korolev, A. Safiullin, M. Belyaev, and Y. Dodonova, “Residual and plain CNN for 3D brain MRI classification.” Jan 2017 [Online] Available: htttps://arxiv.org/abs/1701.06643
[8] E.Ben George, M.Karnan, "MRI BrainImage EnhancementUsingFilteringTechniques", International Journal ofComputer Science & Engineering Technology, IJCSET, 2012.
[9] Daljit Singh, Kamaljeet Kaur,"Classification of Abnormalities in Brain MRI Images Using GLCM, PCAandSVM",International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-1,Issue-6, August 2012.
[10] Prachi Gadpayleand, P.S. Mahajani, "Detectionand Classification of Brain Tumor in MRI Images ",International Journal of Emerging Trends in Electricaland Electronics, IJETEE – ISSN: 2320-9569, Vol. 5, Issue. 1, July-2013.
[11] Shweta Jain, "Brain Cancer ClassificationUsing GLCM Based Feature Extraction in Artificial Neural Network" , International Journal of Computer Science & Engineering Technology ,IJCSET, ISSN : 2229-3345Vol. 4 No. 07 Jul 2013.
[12] WalaaHusseinIbrahim,Ahmed Abdel Rhman Ahmed Osman, Yusra Ibrahim Mohamed, "MRI BrainImageClassification Using Neural Networks" ,IEEE InternationalConference On Computing, Electricaland ElectronicsEngineering,ICCEEE,2013.
[13] Mehdi Jafari, Reza Shafaghi, "A Hybrid Approach for Automatic Tumor Detection of Brain MRI using Support Vector Machine and Genetic Algorithm", Global Journal of Science Engineeringand Technology, Issue-3, 2012.
[14] Noramalina Abdullah, Lee Wee Chuen,UmiKalthumNgah KhairulAzman Ahmad, "Improvement of MRI Brain Classification using Principal Component Analysis", IEEE International Conference on Control System, Computing and Engineering, 2011.
[15] Suchita Goswami, Lalit Kumar P. Bhaiya, " Brain Tumor Detection Using Unsupervised Learning based Neural Network", IEEE International Conference on Communication Systems and Network Technologies,2013.