Brain Tumor Segmentation from MRI Images Using Morphological Operation

Authors

  • Bappa Sarkar Islamic University, Kushtia, Bangladesh
  • Abdullah Al Zubaer Islamic University, Kushtia, Bangladesh
  • Joyassree Sen Islamic University, Kushtia, Bangladesh
  • Md. Nazrul Islam Islamic University, Kushtia, Bangladesh

Keywords:

MRI Image, Morphological operation, Brain tumor segmentation, Opening (Morphology).

Abstract

Medical image processing is the most important and challenging field now a days. MRI image processing is one of the parts of this field. Brain tumor segmentation in magnetic resonance imaging (MRI) has become an emergent research area in the field of a medical imaging system. Brain tumor analysis is done by the doctor of which the conclusion may vary from one doctor to another. To ease doctor judgment, in this paper we have applied some morphological operation on tumor shape and extracted the tumor area using MATLAB. Furthermore, we have calculated the affected area of tumor shape and then saved the result for the next observation with a unique id for a specific patient. After a few weeks, when the patient will come for the next observation, again our system will take a unique id and recent MRI image of the affected patient for showing the result after calculating the previous and present results. Our system totally removes the doctor's insipidness and abstains from the wrong diagnosis.

Downloads

Download data is not yet available.

Author Biographies

Bappa Sarkar, Islamic University, Kushtia, Bangladesh

Assistant Professor, Department of Computer Science and Engineering

Abdullah Al Zubaer, Islamic University, Kushtia, Bangladesh

Assistant Professor, Department of Computer Science and Engineering

Joyassree Sen, Islamic University, Kushtia, Bangladesh

Assistant Professor, Department of Computer Science and Engineering

Md. Nazrul Islam, Islamic University, Kushtia, Bangladesh

Assistant Professor, Department of Computer Science and Engineering

References

Halder, A., Pradhan, A., Dutta, S.K. and Bhattacharya, P., 2016, April. Tumor extraction from MRI images using dynamic genetic algorithm based image segmentation and morphological operation. In 2016 International Conference on Communication and Signal Processing (ICCSP) (pp. 1845-1849). IEEE.

Vishnumurthy, T.D., Mohana, H.S. and Meshram, V.A., 2016, December. Automatic segmentation of brain MRI images and tumor detection using morphological techniques. In 2016 international conference on electrical, electronics, communication, computer and optimization techniques (ICEECCOT) (pp. 6-11). IEEE.

Halder, A., Giri, C. and Halder, A., 2014, January. Brain tumor detection using segmentation based Object labeling algorithm. In International Conference on Electronics, Communication and Instrumentation (ICECI) (pp. 1-4). IEEE.

Ramya, L. and Sasirekha, N., 2015, March. A robust segmentation algorithm using morphological operators for detection of tumor in MRI. In 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS) (pp. 1-4). IEEE.

Thakur, P., Pahwa, K. and Gupta, R., 2015. Brain tumor detection segmentation using watershed segmentation and morphological operation. International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE), 4(6).

Oo, S.Z. and Khaing, A.S., 2014. Brain tumor detection and segmentation using watershed segmentation and morphological operation. International Journal of Research in Engineering and Technology, 3(03), pp.367-374.

El-Dahshan, E.S.A., Mohsen, H.M., Revett, K. and Salem, A.B.M., 2014. Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm. Expert systems with Applications, 41(11), pp.5526-5545.

Dhumal, S.P. and Gaikwad, A.S., 2014. Automated Brain Tumor Segmentation Using Region Growing Algorithm by Extracting Feature. International Journal of Application or Innovation in Engineering and Management (IJAIEM), 3(12), pp.121-127.

Rana, R., Bhdauria, H.S. and Singh, A., 2013, August. Brain tumour extraction from MRI images using bounding-box with level set method. In 2013 Sixth International Conference on Contemporary Computing (IC3) (pp. 319-324). IEEE.

[Roy, S., Chatterjee, K., Maitra, I.K. and Bandyopadhyay, S.K., 2013. Artefact Removal from MRI of Brain Image. International Refereed Journal of Engineering and Science (IRJES), 2(3), pp.24-30.

[Roy, S., Nag, S., Maitra, I.K. and Bandyopadhyay, S.K., 2013. Artefact removal and skull elimination from MRI of brain image. International Journal of Scientific and Engineering Research, 4(6), pp.163-170.

Gordillo, N., Montseny, E. and Sobrevilla, P., 2013. State of the art survey on MRI brain tumor segmentation. Magnetic resonance imaging, 31(8), pp.1426-1438.

Patil, R.C. and Bhalchandra, A.S., 2012. Brain tumour extraction from MRI images using MATLAB. International Journal of Electronics, Communication & Soft Computing Science and Engineering, 2(1), pp.1-4.

Mustaqeem, A., Javed, A. and Fatima, T., 2012. An efficient brain tumor detection algorithm using watershed & thresholding based segmentation. International Journal of Image, Graphics and Signal Processing, 4(10), p.34.

Abdullah, N., Ngah, U.K. and Aziz, S.A., 2011, May. Image classification of brain MRI using support vector machine. In 2011 IEEE International Conference on Imaging Systems and Techniques (pp. 242-247). IEEE.

Downloads

Published

2020-08-30

How to Cite

Bappa Sarkar, Abdullah Al Zubaer, Joyassree Sen, & Md. Nazrul Islam. (2020). Brain Tumor Segmentation from MRI Images Using Morphological Operation. Computer Reviews Journal, 7, 1-6. Retrieved from https://purkh.com/index.php/tocomp/article/view/826

Issue

Section

Research Articles