4

Brain Tumor Detection Using Image

Processing Techniques

Kristin Surpuhi Benli

Üsküdar University, İstanbul, Türkiye

A brain tumor impairs the body’s ability to operate normally and is a po-

tentially fatal condition. Early diagnosis and effective treatment planning are

contingent upon the early detection of brain tumors. The role of MRI scan-

ning in medical research has become increasingly prominent over the past few

years. Medical image analysis heavily relies on digital image processing. The

image segmentation process is of paramount importance in image processing,

as it facilitates the extraction of data from intricate medical images. The seg-

mentation of brain tumors involves the separation of abnormal brain tissue

(tumor) from the healthy brain tissue. Several researchers have previously

proposed techniques for detecting and segmenting brain tumors. An overview

of the techniques to detect brain tumors through MRI image segmentation

is provided in this book chapter. This book chapter is composed of five sec-

tions: Section I gives a brief introduction about the brain tumor detection

study. Section II explains magnetic resonance imaging. Section III describes

the brain tumor detection stages; pre-processing, skull stripping, and various

segmentation techniques. Section IV discusses an overview of prior researches

and Section IV concludes the book chapter.

4.1

Introduction

It is essential, as with all types of cancer, to detect the presence of brain

cancer early in order to ensure the survival of patients. The brain tumor is

caused by the uncontrolled proliferation of certain cells in the brain or around

it. Magnetic Resonance Imaging (MRI) is one of the most widely utilized and

favored electronic modalities for the diagnosis of brain tumors. It provides an

evaluation of the lesion by taking high-resolution and contrast images of the

DOI: 10.1201/9781003461906-4

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