Mahsa Akhbari

High-performance brain tumor classification via transfer learning with fully fine-tuned and modified CNN architectures

Accurate and timely brain tumor diagnosis remains challenging due to the limitations of manual MRI interpretation. This study introduces a transfer learning framework using six fully fine–tuned and modified CNN architectures DenseNet169, InceptionV3, Xception, ResNet50, Inception...

A hybrid approach based on deep learning to improve segmentation, classification and localization of different types of brain tumors in MRI images

Brain tumors pose significant health risks, and early detection is critical for improving patient outcomes. Although Magnetic Resonance Imaging (MRI) is widely used for diagnosis, accurate interpretation remains challenging, particularly in resource-limited clinical settings. To...