A Real-Time Approach to Brain Tumor Detection Implementing Wavelets and ANN

Authors

  • Vijay Kumar G Professor, Dept. of CSE, VKR, VNB & AGK College of Engineering, Gudivada, AP, India, Cell No:
  • Raju GV Director, DNR College of Engineering and Technology Bhimawaram, West-Godavari Dist., AP. India, Cell No:

Keywords:

Magnetic Resonance Spectroscopic Imaging, Wavelet, Wavelet Packets, Artificial Neural Networks, Tumor, Necrosis

Abstract

Functional Magnetic Resonance Imaging (fMRI) is a non-invasive technique for assessing tumor detection. The need to differentiate between normal and abnormal tissues and determine type of abnormality before biopsy or surgery motivated development and application of fMRI. There are several technical reasons that make the brain easier than other organs to be examined with fMRI. This paper presents our proposed methods and results for the analysis of the brain spectra of patients with three tumor types. After extracting features from fMRI data using wavelet and wavelet packets, artificial neural networks are used to determine the abnormalities in the Tumor and the type. The proposed methods like clinical and simulated fMRI data and biopsy results. The fMRI analysis results were correct 97% of the time when classifying the spectra of the clinical fMRI data into normal tissue, tumor. and radiation necrosis.

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Published

2025-11-11

How to Cite

[1]
G. Vijay Kumar and G. Raju, “A Real-Time Approach to Brain Tumor Detection Implementing Wavelets and ANN”, Int. J. Comp. Sci. Eng., vol. 3, no. 11, pp. 89–93, Nov. 2025.

Issue

Vol. 3 No. 11 (2015): IJCSE November Edition

Section

Review Article

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