ANALYSIS OF BRAIN MRI SEGMENTATION TECHNQIUES FOR DETECTION OF DISEASES

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MALVIKA SHARMA
Prabhpreet Kaur

Abstract

The MRI (Magnetic Resonance Imaging) is diagnosis tool for detection of tumor in brain as it uses magnets to produce magnetic field and radio waves to generate images of brain and also used to analyse it. The abnormal growth of cells or tissues is known as tumor, the presence of tumor can be detected by help MR images. The use of digital image processing is to be done in order to analysis the MR image. The various techniques of image processing such as image acquisition, pre-processing, feature extraction, image classification etc. are utilized for analysis of magnetic images. The segmentation is one of the technique that partition digital image into multiple segments .it is used to locate the lines, curves and objects in the image. The survey of various techniques that are based on segmentation of MR images are to be done in this paper.

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Author Biographies

MALVIKA SHARMA, Guru Nanak Dev University, Amritsar

Mtech student at Guru Nanak Dev University, Amritsar

Prabhpreet Kaur, Guru Nanak Dev University, Amritsar

Assistant Professor at Guru Nanak Dev University, Amritsar

References

Advisor, Dissertation and Dissertation Committee. 2007. “Communication Security in Wireless Sensor.†DOI: https://doi.org/10.1023/A:1019968506856

Bhima, K. and A. Jagan. 2016. “Analysis of MRI Based Brain Tumor Identification Using Segmentation Technique.†2109–13.DOI: 10.1109/ICCSP.2016.7754551

Deshmukh, Ruchi D. 2014. “Study of Different Brain Tumor MRI Image Segmentation Techniques.†4(4):133–36.

Engineering, Communication. 2012. “2012 International Conference on Computing Sciences LUNG CANCER DETECTION ON CT IMAGES BY USING IMAGE PROCESSING.†142–46.DOI: 10.1109/SCEECS.2014.6804437

Lal, Anisha M. and D. Aju. 2014. “Abnormality Extraction of MRI Brain Images Using Region Growing Segmentation Techniques.†3(8):76–82. http://www.erpublications.com/uploaded_files/download/download_16_08_2014_15_28_09.pdf

Manju, D., M. Seetha, and K. Venugopala Rao. 2013. “Comparison Study of Segmentation Techniques for Brain Tumour Detection.†2:261–69.

Mingoti, Sueli a. and Joab O. Lima. 2006. “Comparing SOM Neural Network with Fuzzy c-Means, K-Means and Traditional Hierarchical Clustering Algorithms.†European Journal of Operational Research 174:1742–59.DOI: 10.1109/SCEECS.2014.6804437

Rao, Prajwal, Nishal Ancelette Pereira, and Raghuram Srinivasan. 2016. “Convolutional Neural Networks for Lung Cancer Screening in Computed Tomography ( CT ) Scans.†489–93.DOI: 10.1109/IC3I.2016.7918014

Satone, Manisha and Gajanan Kharate. 2014. “Feature Selection Using Genetic Algorithm for Face Recognition Based on PCA , Wavelet and SVM.†6(1):39–52.DOI: 10.15676/ijeei.2014.6.1.3

Selvanayaki, K. and P. Kalugasalam. 2013. “Available Online at Www.jgrcs.info INTELLIGENT BRAIN TUMOR TISSUE SEGMENTATION FROM MAGNETIC RESONANCE IMAGE ( MRI ) USING META HEURISTIC ALGORITHMS.†4(2):13–20.

Selvaraj, D. 2013. “MRI BRAIN IMAGE SEGMENTATION TECHNIQUES - A REVIEW.†4(5):364–81.DOI: https://doi.org/10.1007/s10462-010-9155-0

Serra, Jean, Luc Vincent, Centre De Morphologie Math, and Ecole Nationale Sup. 1992. “An Overview of Morphological Filtering.†Circuits, Systems and Signal Processing 11(1):47–108. DOI: https://doi.org/10.1007/BF01189221

Sharma, Abhilasha, Amit Kumar Singh, and S. P. Ghrera. 2015. “Secure Hybrid Robust Watermarking Technique for Medical Images.†Procedia Computer Science 70:778–84. Available at: http://www.sciencedirect.com/science/article/pii/S1877050915032810

T, Ivana Despotovi, Bart Goossens, and Wilfried Philips. 2015. “MRI Segmentation of the Human Brain : Challenges , Methods , and Applications.†2015. DOI: 10.1155/2015/450341

Takeuchi, Hiroshi and Naoki Kodama. 2014. “Validity of Association Rules Extracted by Healthcare-Data-Mining.†Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2014(1):4960–63.DOI: 10.1109/EMBC.2014.6944737

Tambe, Pallavi. 2016. “Comparative Study of Segmentation Techniques for Brain Tumor Detection.†5(02):269–71. DOI: 10.17485/ijst/2016/v9i4/85624

Tichkule, Shivani K. 2016. “Plant Diseases Detection Using Image Processing Techniques.†1–6.DOI: 10.1109/GET.2016.7916653.

Tirpude, Neha and R. R. Welekar. 2013. “A Study of Brain Magnetic Resonance Image Segmentation Techniques.†2(1). Available at: https://www.ijarcce.com/upload/january/14-A%20Study%20of%20Brain%20Magnetic.pdf

Xie, Zhicheng, Kun Yu, Shu Su, Zhengtian Li, and Xiangning Lin. 2016. “Fault Diagnosis Method of Transformer Based on Cloud Theory and Entropy Weight.†337–41.DOI: 10.1109/SEGE.2016.7589548

Yan, Zhiyong and Congfu Xu. 2010. “Combining KNN Algorithm and Other Classifiers.†Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010 (1):800–805.DOI: 10.1109/SERA.2005.30.