Subject Review: Brain Tumor Detection Techniques

Authors

  • Wedad Abdul Khuder Naser Mustansiriyah University, Baghdad, Iraq

DOI:

https://doi.org/10.31695/IJERAT.2021.3722

Keywords:

Brain tumor, MRI images, Segmenting, Detection accuracy

Abstract

A brain tumor is one of the main causes of increased mortality among children and adults. The tumor is a major problem that is out of control over the normal force that regulates growth. There are several techniques for segmenting and detecting a brain tumor area on MRI images. In this paper, we provide background reviews of several proposed techniques for the recognition of brain tumors. There is a lot of literature on detecting this type of brain tumor and improving detection accuracy.

References

] Amit M., Yee K. T., Stephen J., Michael A., and Frederik L., “An Introduction to Tumor Brain Imagining “, Springer, 2014

J.Seetha and Selvakumar Raja . , “Brain Tumor Classification Using Convolution Neural Network ”, Biomedical & Pharmacology Journal, September 2018, Vol 11(3), p . 1457-1461

Ahmed K., Karim G., “Hybrid Approach for Automatic Classification of Brain MRI Using Genetic Algorithm and Support Vector Machine “, Leonardo Journal of Sciences, pp.71-82,2010.

Janani and P. Meena, “image segmentation for tumor detection using fuzzy inference system”, International Journal of Computer Science and Mobile Computing, 2(5): 244 – 248 (2013).

Meiyan Huang et al, “Brain Tumor Segmentation Based on Local Independent Projection-based Classification”, IEEE Transactions on Biomedical Engineering, IEEE, (2013).

R. Karuppathal and V. Palanisamy, “Fuzzy based automatic detection and classification approach for MRI-brain tumor”, ARPN Journal of Engineering and Applied Sciences, 9(12): (2014).

Marco Alfonse and Abdel- Badeeh M. Salam, “ An Automatic Classification of Brain Tumor through MRI Using Support Vector Machine . “, Egyptian Computer Science Journal(ISSN:1110-2586), Volume 40-ISSUE 03, September 2016.

Heba Mohsen et al, “Classification using Deep Learning Neural Networks for Brain Tumors”, Future Computing and Informatics, pp 1-4 (2017)

Abbas, Qaiser, et al “ Mango Classification Using Texture &Shape Features “, International Journal of computer science and network security 18.8:132-138,2018.

Anjali, V. Charan, and Shanthi Prince. , “ A novel methodology for brain tumor detection based on two-stage segmentation of MRI images .”, Advanced Computing and Communication System, International Conference on IEEE,2015.

AndacHamamci et al, “Tumor-Cut: Segmentation of Brain Tumors on Contrast-Enhanced MR Images for Radiosurgery Applications”, IEEE Transactions on Medical Imaging, 31(3): (2012).

Stefan Bauer et al, “Multiscale Modeling for Image Analysis of Brain Tumor Studies”, IEEE Transactions on Biomedical Engineering, 59(1): (2012)

Shree, N. Varuna, and T.N.R. Kumar. ”Identification and classification of brain tumor MRI image with feature extraction using DWT and probabilistic neural network.” Brain informatics 5.1:23-30, 2018.

Gupta, Shefali, et al . “ Segmentation, Feature Extraction and Classification of Astrocytoma in MR Images .“ Indian Journal of Science and Technology 9.36:1-8, 2016.

Isselmou, A., Shuai Zhang, and Guizhi Xu “A novel approach for brain tumor detection using MRI images .” J Biomed Sci Eng. 9:44-52,2016.

Bjoern H. Menze et al, “The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)”, IEEE Transactions on Medical Imaging, (2014).

Atiq Islam et al, “Multi-fractal Texture Estimation for Detection and Segmentation of Brain Tumors”, IEEE, (2013).

Shamsul Huda et al, “A Hybrid Feature Selection with Ensemble Classification for Imbalanced Healthcare Data: A Case Study for Brain Tumor Diagnosis”, IEEE Access, 4: (2017).

Jin Liu et al, “A Survey of MRI-Based Brain Tumor Segmentation Methods”, TSINGHUA Science and Technology, 19(6) (2011).

A. Jayachandran and R. Dhanasekaran, “Brain Tumor Detection And Classification of MR Images Using Texture Features And Fuzzy SVM Classifier “, Research Journal of Applied Sciences, Engineering and Technology 6(12), 2264-2269, 2013.

Downloads

Published

2021-08-05

Issue

Section

Articles

How to Cite

Subject Review: Brain Tumor Detection Techniques . (2021). International Journal of Engineering Research and Advanced Technology (ijerat) (E-ISSN 2454-6135) DOI: 10.31695 IJERAT, 7(8), 1-4. https://doi.org/10.31695/IJERAT.2021.3722