Probability based Watershed Segmentation Algorithm for Multiple Brain Tumor Detection

Authors

  • Busa S Department of CSE, Acharya Nagarjuna University., Guntur, A.P, India
  • Reddy ES Department of CSE, A.N.U. College of Engineering & Technology, Acharya Nagarjuna University., Guntur, A.P, India

DOI:

https://doi.org/10.26438/ijcse/v6i12.955960

Keywords:

PWS, Brain, Tumor, Noise reduction, MRI Images

Abstract

Automatic tumor detection is one of the difficult tasks in medical image diagnosis due to variations in size, type, shape and location of tumors. In the traditional brain tumor detection models, intra and inter slice resolutions may affect the segmentation accuracy. In addition, brain tumors have different intensities overlapping with normal tissue. In this paper, we have proposed an automatic tumor detection framework to detect the multiple tumors in brain tumor databases. This system has three main phases, namely image preprocessing, iterative threshold image enhancement and multi tumor segmentation algorithm. Experimental results show that our proposed system efficiently detects multiple tumors at different locations in the brain tumor image dataset.

References

[1] Amsaveni, V.; Singh, N. Albert," Detection of brain tumor using neural network" Institute of Electrical and Electronics Engineers – Jul 4, 2013.

[2] Tulsani, Saxena, Mamta, " Comparative study of techniques for brain tumor segmentation", IEEE, Nov 23,2013.

[3] Dhage, Phegade, Shah," Watershed segmentation brain tumor detection", IEEE, 2015.

[4] Francis, Premi," Kernel Weighted FCM based MR image segmentation for brain tumor detection",IEEE,2015.

[5] Badmera, Nilawar, Anil," Modified FCM approach for MR brain iamge segmentation", IEEE,2013.

[6] Hanuman Verma, Ramesh, " Improved Fuzzy entropy clustering algorithm for MRI Brain image segmentation", IJIST, 2014.

[7] S.Luo, "Automated Medical image segementation using a new deformable surface model", IJCSNS,2006.

[8] Gordiallo, Eduard," State of the art survey on MRI Brain tumor segmentation" , Magnetic resonance imaging,2013.

[9] Tang, Welping,"Tumor segmentation form single constrast MR images of human brain”, IEEE,2015

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Published

2018-12-31
CITATION
DOI: 10.26438/ijcse/v6i12.955960
Published: 2018-12-31

How to Cite

[1]
S. Busa and E. Reddy, “Probability based Watershed Segmentation Algorithm for Multiple Brain Tumor Detection”, Int. J. Comp. Sci. Eng., vol. 6, no. 12, pp. 955–960, Dec. 2018.

Issue

Vol. 6 No. 12 (2018): IJCSE December Editor

Section

Research Article

License

Creative Commons License

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