14: Deep autoencoder-based automated brain tumor detection from MRI data
Fatih Demir Biomedical Department, Vocational School of Technical Sciences, Firat University, Elazig, Turkey
Abstract
Brain tumor detection from magnetic resonance (MR) image samples is the core way for radiologists, specialists, and physicians. Artificial intelligence-based MR image classification can make a great contribution to the decision-making process of physicians due to both healthcare personnel shortages and workload. Deep learning approaches are frequently used since they have high performance in medical image classification tasks. In this study, a novel and effective method based on a deep autoencoder was proposed for brain tumor detection from ...
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