Analysis of Selected Binarization Techniques for Brain Tumor Magnetic Resonance Images

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Date

2023

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Institute of Electrical and Electronics Engineers Inc.

Abstract

The identification and therapy of brain tumors have greatly improved as a result of recent developments in the field of medical imaging. Among the different imaging techniques, magnetic resonance imaging (MRI) is essential for identifying and describing brain tumors. However, accurately segmenting tumor regions from MRI scans remains a persistent challenge due to tumors' complex and diverse appearances. To address this challenge, extensive evaluation of novel approaches and comparative analysis of existing methods are essential to unlock the potential of binarization techniques. This paper presents the transformative capacity of binarization techniques in elevating overall brain tumor management. We select a set of binarization techniques for MRIs. The methods are implemented to find a better approach that can be employed for better segmentation and detection of brain tumors from the input MRI dataset. Consequently, we propose an alternative binarization technique. Through precise and personalized healthcare interventions, the proposed approach holds promise for enhancing patient outcomes and improving the quality of life for individuals affected by brain tumors. © 2023 IEEE.

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Keywords

Brain Tumor, Image Binarization, K-Means Clustering, MRI Image, Thresholding

Citation

2023 IEEE 20th India Council International Conference, INDICON 2023, 2023, Vol., , p. 1100-1105

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