BRAIN TUMOR DETECTION USING IMAGE SEGMENTATION
ABSTRACT
Using Mathematical Morphological Reconstruction, this study proposes a computer-aided detection approach for diagnosing brain tumors in their early stages (MMR). The image is pre-processed to remove noise and artifacts before being segmented to identify regions of interest with possible tumors.
To determine whether the brain tumor in the image is benign or malignant, a large number of textural and statistical features are extracted from the segmented image. The experimental results show that the segmented images have a high accuracy while reducing computation time significantly. The study demonstrates that the proposed solution can be used to successfully diagnose brain tumors in patients.
INTRODUCTION
Computer-aided detection (CAD) of brain tumors is a preferred tool for non-invasive brain tumor diagnosis [1].
Magnetic Resonance Imaging (MRI) is used to obtain the brain images, which are susceptible to noise and artifacts such as labels and intensity variations during acquisition [2]. Aside from the tumor, the brain image contains many structures such as cerebrospinal fluid, grey matter, white matter, and skull tissues [3].
A generic CAD brain tumor detection process includes the following steps: pre-processing the image to remove noise and artifacts, segmenting the pre-processed image to identify potential tumor regions, extracting useful features from the tumor regions, and classifying whether or not a tumor is present [4].
Watershed segmentation [5, 6, 7], mathematical morphology [8, Fuzzy Cmeans, and neural networks [1] are some of the segmentation techniques used to diagnose brain cancer. Despite certain benefits, the most common issue with current techniques is their inability to predict brain tumors with high accuracy.
The goal of this study is to address the limitations mentioned above in existing methods– to improve the accuracy of brain tumor detection using image processing tools and to reduce the computation time of the steps involved so that a brain MRI image can be identified as malignant or benign in the shortest computation time possible.
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BRAIN TUMOR DETECTION USING IMAGE SEGMENTATION
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