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The aim is to develop a hybrid method for accurate brain tumor extraction and effective MRI classification.

April 21, 2026Open Access

Hybrid method for brain tumor extraction and MRI scan classification

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Machine learning classifies MRI scans as normal or abnormal, indicating improved tumor detection methods.

The aim is to develop a hybrid method for accurate brain tumor extraction and effective MRI classification.
Utilized machine learning algorithms: Support Vector Machine, Linear Discriminant Analysis, and Artificial Neural Network for MRI classification.
Applied morphological operations, filtering, and histogram processing for tumor region detection from abnormal MRI scans.
Tested classification methods on a large dataset to assess accuracy.
Achieved classification accuracies of 93.06% for SVM, 97.45% for LDA, and 98.9% for ANN.
Demonstrated effective detection of brain tumor regions using a hybrid approach, enhancing diagnosis capabilities.
Highlighted the potential for advanced imaging techniques to improve early tumor detection.

Elsayed et al. (2026) studied this question.

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