A review on various brain tumor detection techniques in brain MRI images

Magnetic resonance imaging is important imaging technique used in the detection of brain tumor. Brain tumor is one of the most dangerous diseases occurring among the human beings. Brain MRI plays a very important role for radiologists to diagnose and treat brain tumor patients. Study of the medical image by the radiologist is a time consuming process and also the accuracy depends upon their experience. Thus, the computer aided systems becomes very necessary as they overcome these limitations. Several automated methods are available, but automating this process is very difficult because of different appearance of the tumor among the different patients. There are various feature extraction and classification methods which are used for detection of brain tumor from MRI images. In this paper, various approaches are reviewed enlightening the advantages and disadvantages of these methods.

[1]  Shweta Jain,et al.  Brain Cancer Classification Using GLCM Based Feature Extraction in Artificial Neural Network , 2013 .

[2]  R. Suja Mani Malar,et al.  Rough set theory and feed forward neural network based brain tumor detection in magnetic resonance images , 2013, International Conference on Advanced Nanomaterials & Emerging Engineering Technologies.

[3]  Shivani Khurana,et al.  Brain Tumor Detection Using Neural Network , 2022 .

[4]  Vignesh Rajesh,et al.  Brain Tumor Segmentation and its Area Calculation in Brain MR Images using K-Mean Clustering and Fuzzy C-Mean Algorithm , 2015 .

[5]  Walaa Hussein Ibrahim,et al.  MRI brain image classification using neural networks , 2013, 2013 INTERNATIONAL CONFERENCE ON COMPUTING, ELECTRICAL AND ELECTRONIC ENGINEERING (ICCEEE).

[6]  P. Natarajan,et al.  Tumor detection using threshold operation in MRI brain images , 2012, 2012 IEEE International Conference on Computational Intelligence and Computing Research.

[7]  Dina M. Aboul Dahab,et al.  Automated Brain Tumor Detection and Identification Using Image Processing and Probabilistic Neural Network Techniques , 2012 .

[8]  Mohd Ariffanan Mohd Basri,et al.  Probabilistic Neural Network for Brain Tumor Classification , 2011, 2011 Second International Conference on Intelligent Systems, Modelling and Simulation.

[9]  Qingmin Liao,et al.  Statistical Structure Analysis in MRI Brain Tumor Segmentation , 2007, Fourth International Conference on Image and Graphics (ICIG 2007).

[10]  V. M. Misra,et al.  Classification of Brain Cancer using Artificial Neural Network , 2010, 2010 2nd International Conference on Electronic Computer Technology.

[11]  S. Goswami,et al.  Brain Tumour Detection Using Unsupervised Learning Based Neural Network , 2013, 2013 International Conference on Communication Systems and Network Technologies.

[12]  R. J. Ramteke,et al.  Automatic Medical Image Classification and Abnormality Detection Using K-Nearest Neighbour , 2012 .

[13]  Navneet Kaur Comparative Analysis of Various Edge Detection Techniques , 2013 .

[14]  P. S. Mahajani,et al.  Detection and Classification of Brain Tumor in MRI Images , 2013 .

[15]  Sudheer Raja Venishetty,et al.  MRI Brain Image Segmentation Using Modified Fuzzy C-Means Clustering Algorithm , 2011, 2011 International Conference on Communication Systems and Network Technologies.

[16]  Mudassar Raza,et al.  Enhanced Watershed Image Processing Segmentation , 2008 .

[17]  Kamaljeet Kaur,et al.  Classification of Abnormalities in Brain MRI Images using GLCM, PCA and SVM , 2012 .

[18]  T. Sree Sharmila,et al.  Efficient quality analysis of MRI image using preprocessing techniques , 2013, 2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES.

[19]  Safaa E. Amin,et al.  Brain tumor diagnosis systems based on artificial neural networks and segmentation using MRI , 2012, 2012 8th International Conference on Informatics and Systems (INFOS).

[20]  Pradeep M. Patil,et al.  Detection and Classification of Brain Tumors , 2015 .

[21]  T. Arivoli,et al.  Brain tumor segmentation and its area calculation in brain MR images using K-mean clustering and Fuzzy C-mean algorithm , 2012, IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012).

[22]  Umi Kalthum Ngah,et al.  Improvement of MRI brain classification using principal component analysis , 2011, 2011 IEEE International Conference on Control System, Computing and Engineering.

[23]  V. Salai Selvam,et al.  Brain tumor detection using scalp eeg with modified Wavelet-ICA and multi layer feed forward neural network , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[24]  E. Ben George,et al.  MRI Brain Image Enhancement Using Filtering Techniques , 2012 .