Thursday 28th of March 2024
 

GLCM textural features for Brain Tumor Classification


N S Zulpe and V P Pawar

Automatic recognition system for medical images is challenging task in the field of medical image processing. Medical images acquired from different modalities such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), etc which are used for the diagnosis purpose. In the medical field, brain tumor classification is very important phase for the further treatment. Human interpretation of large number of MRI slices (Normal or Abnormal) may leads to misclassification hence there is need of such a automated recognition system, which can classify the type of the brain tumor. In this research work, we used four different classes of brain tumors and extracted the GLCM based textural features of each class, and applied to two-layered Feed forward Neural Network, which gives 97.5% classification rate.

Keywords: MRI, CT, GLCM, Neural Network

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ABOUT THE AUTHORS

N S Zulpe
Nitish S Zulpe received the MCS degree from SRTM University, Nanded in the year 2004. He received the M.Phil. Degree in Computer Science from Y.C.M.O. University, Nashik in the year 2009. He is currently working as lecturer in the College of Computer Science and Information Technology, Latur, Maharastra. He is leading to PhD degree in University of Pune.

V P Pawar
Vrushsen Pawar received MS, Ph.D.(Computer) Degree from Dept .CS & IT, Dr.B.A.M. University & PDF from ES, University of Cambridge, UK. Also Received MCA (SMU), MBA (VMU) degrees respectively. He has received prestigious fellowship from DST, UGRF (UGC), Sakaal foundation, ES London, ABC (USA) etc. He has published 90 and more research papers in reputed national international Journals & conferences. He has recognize Ph.D Guide from University of Pune, SRTM University & Sighaniya University (India). He is senior IEEE member and other reputed society member. Currently working as a Asso. Professor in CS Dept. SRTMU, Nanded.


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