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2024 | OriginalPaper | Buchkapitel

AI-Based Smart Decision System for Early and Accurate Brain Tumor Prediction

verfasst von : Anandakumar Haldorai, Babitha Lincy R, Suriya Murugan, Minu Balakrishnan

Erschienen in: Artificial Intelligence for Sustainable Development

Verlag: Springer Nature Switzerland

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Abstract

Radiology is an expansive field that relies on specialized medical knowledge and insights to effectively identify brain tumors. Recent advancements in biomedical image analysis and processing techniques have made it possible to utilize Magnetic Resonance Imaging (MRI) for improved tumor detection. In this study, MRI images were utilized as input to identify the location of brain tumors, employing a segmentation and detection approach. This approach is complicated by the wide variety of tumor tissues seen in people as well as the similarity between normal and tumor tissues. On the other hand, using automated computer-aided techniques can significantly enhance tumor diagnosis. This research presents a deep learning model that uses a faster R-CNN with transfer learning for brain MRI image classification. The proposed method achieves a remarkable 93% classification accuracy, outperforming the other algorithms analyzed in the research.

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Vorheriges Kapitel An Investigation on Different Approaches for Medical Imaging

Nächstes Kapitel Detecting Alzheimer’s Disease Using Deep Learning Framework for Medial IoT Application

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Titel: AI-Based Smart Decision System for Early and Accurate Brain Tumor Prediction
verfasst von: Anandakumar Haldorai
Babitha Lincy R
Suriya Murugan
Minu Balakrishnan
Verlag: Springer Nature Switzerland
Buch: Artificial Intelligence for Sustainable Development
Print ISBN: 978-3-031-53971-8

Electronic ISBN: 978-3-031-53972-5

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-3-031-53972-5_4

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