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Digital Image Watermarking Using Sine Transform Technique Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Fusion-Based Segmentation Technique for Improving the Diagnosis of MRI Brain Tumor in CAD Applications

Authors : Bharathi Deepa, Manimegalai Govindan Sumithra, Venkatesan Chandran, Varadan Gnanaprakash

Published in: Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)

Publisher: Springer International Publishing

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Abstract

Diagnosing the brain tumor from Magnetic Resonance Imaging (MRI) in Computer-Aided Diagnosis (CAD) applications is one of the challenging task in medical image processing. Traditionally many segmentation methods are used to address this issue. This paper introduces a segmentation method along with image fusion. Here a Discrete Wavelet Transform (DWT) method is chosen, for image fusion followed by segmentation using Support Vector Machine (SVM) for detecting the abnormality region. The types of MRI images considered here include T1-weighted (T1-w), T2-weighted (T2-w) and FLAIR images. The various fusion combinations are T1-w and T2-w, T1-w and FLAIR, T2-w and FLAIR. Experimental results suggest that on an average, fusion-based segmented result is superior to non-fusion-based segmented result.

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Metadata
Title
Fusion-Based Segmentation Technique for Improving the Diagnosis of MRI Brain Tumor in CAD Applications
Authors
Bharathi Deepa
Manimegalai Govindan Sumithra
Venkatesan Chandran
Varadan Gnanaprakash
Copyright Year
2019
Book
Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)

Print ISBN: 978-3-030-00664-8

Electronic ISBN: 978-3-030-00665-5

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-00665-5_31