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2021 | OriginalPaper | Chapter

1. Computational Intelligence for Brain Tumors Detection

Author : Abdel-Badeeh M. Salem

Published in: New Approaches for Multidimensional Signal Processing

Publisher: Springer Singapore

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Abstract

Recently, computational intelligence (CI) techniques have become efficient intelligent tools for brain tumor detection. It has become one of the major research subjects in medical imaging and diagnostic radiology. In the area of processing the brain images, computer-aided diagnosis (CAD) systems are basically relied on different CI techniques in all its stages to implement a smart consultation system that can help the radiologists by providing a second opinion that can assist in detection and diagnosis of brain tumors. This paper presents a comprehensive and up-to-date research in the area of digital medical imaging covering a wide spectrum of CI methodological and intelligent algorithm. The paper discusses the current research of the CI techniques for developing smart CAD systems. We present two applications for a hybrid intelligent technique for automatic detection of brain tumor through MRI. The technique is based on the following CI methods: the feedback pulse-coupled neural network for image segmentation, the discrete wavelet transform for features extraction, the principal component analysis for reducing the dimensionality of the wavelet coefficients, and the feed-forward back-propagation neural network to classify inputs into normal or abnormal.

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Title: Computational Intelligence for Brain Tumors Detection
Author: Abdel-Badeeh M. Salem
Publisher: Springer Singapore
Book: New Approaches for Multidimensional Signal Processing
Print ISBN: 978-981-334-675-8

Electronic ISBN: 978-981-334-676-5

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-981-33-4676-5_1

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