Academic Journal

Advanced AI-driven approach for enhanced brain tumor detection from MRI images utilizing EfficientNetB2 with equalization and homomorphic filtering

التفاصيل البيبلوغرافية
العنوان: Advanced AI-driven approach for enhanced brain tumor detection from MRI images utilizing EfficientNetB2 with equalization and homomorphic filtering
المؤلفون: A. M. J. Zubair Rahman, Muskan Gupta, S. Aarathi, T. R. Mahesh, V. Vinoth Kumar, S. Yogesh Kumaran, Suresh Guluwadi
المصدر: BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-19 (2024)
بيانات النشر: BMC, 2024.
سنة النشر: 2024
المجموعة: LCC:Computer applications to medicine. Medical informatics
مصطلحات موضوعية: Artificial intelligence, Healthcare, MRI imaging, Brain tumor detection, EfficientNetB2, Image preprocessing, Computer applications to medicine. Medical informatics, R858-859.7
الوصف: Abstract Brain tumors pose a significant medical challenge necessitating precise detection and diagnosis, especially in Magnetic resonance imaging(MRI). Current methodologies reliant on traditional image processing and conventional machine learning encounter hurdles in accurately discerning tumor regions within intricate MRI scans, often susceptible to noise and varying image quality. The advent of artificial intelligence (AI) has revolutionized various aspects of healthcare, providing innovative solutions for diagnostics and treatment strategies. This paper introduces a novel AI-driven methodology for brain tumor detection from MRI images, leveraging the EfficientNetB2 deep learning architecture. Our approach incorporates advanced image preprocessing techniques, including image cropping, equalization, and the application of homomorphic filters, to enhance the quality of MRI data for more accurate tumor detection. The proposed model exhibits substantial performance enhancement by demonstrating validation accuracies of 99.83%, 99.75%, and 99.2% on BD-BrainTumor, Brain-tumor-detection, and Brain-MRI-images-for-brain-tumor-detection datasets respectively, this research holds promise for refined clinical diagnostics and patient care, fostering more accurate and reliable brain tumor identification from MRI images. All data is available on Github: https://github.com/muskan258/Brain-Tumor-Detection-from-MRI-Images-Utilizing-EfficientNetB2 ).
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1472-6947
Relation: https://doaj.org/toc/1472-6947
DOI: 10.1186/s12911-024-02519-x
URL الوصول: https://doaj.org/article/90abd025465149b196d1c30b7d02d366
رقم الانضمام: edsdoj.90abd025465149b196d1c30b7d02d366
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:14726947
DOI:10.1186/s12911-024-02519-x