In this paper, a Fully Automatic Heterogeneous Segmentation using Support Vector Machine (FAHS-SVM) has been proposed for brain tumor segmentation based on deep learning techniques. The present work ...

A brain tumor is one aggressive disease. More than 84,000 people will receive a primary brain tumor diagnosis in 2021 and an estimated 18,600 people will die from a malignant brain tumor (brain cancer ...

Sarhan, A. (2020) Brain Tumor Classification in Magnetic Resonance Images Using Deep Learning and Wavelet Transform. Journal of Biomedical Science and Engineering , 13 , 102-112. doi: ...

The original implementation of this work was done using BraTS 2019 dataset (T1 contrast enhanced images) with high-grade and low-grade glioma samples, and using IXI (T1 images), the healthy brain ...

Brain tumour classification: The neural network classifies tumour type based on its image characteristics in the MRI scan. The colour maps show which pixels led to a correct prediction, with warmer ...

A new study published in the Journal of Theoretical Biology demonstrates how AI deep learning can predict brain tumor progression for glioblastoma from medical images to accelerate precision medicine.

Brain tumors pose significant challenges in healthcare due to their complex origins and diverse range of neurological symptoms. It's crucial to quickly and accurately identify and classify these ...