Deep learning-based methods have become the dominant methodology in medical image
processing with the advancement of deep learning in natural image classification, detection …

Abstract Novel Coronavirus disease (COVID-19) has abruptly and undoubtedly changed the
world as we know it at the end of the 2nd decade of the 21st century. COVID-19 is extremely …

Brain tumors are among the most fatal and devastating diseases, often resulting in
significantly reduced life expectancy. An accurate diagnosis of brain tumors is crucial to …

The automated classification of brain tumors plays an important role in supporting
radiologists in decision making. Recently, vision transformer (ViT)-based deep neural …

Convolutional neural network (CNN) is widely used to classify brain tumors with high
accuracy. Since CNN collects features randomly without knowing the local and global …

Detection and Classification of a brain tumor is an important step to better understanding its
mechanism. Magnetic Reasoning Imaging (MRI) is an experimental medical imaging …

Brain tumors can be fatal if not detected early enough. Manually diagnosing brain tumors
requires the radiologist's experience and expertise, which may not always be available …

Medical image classification plays an essential role in clinical treatment and teaching tasks.
However, the traditional method has reached its ceiling on performance. Moreover, by using …

The classification of brain tumors is performed by biopsy, which is not usually conducted
before definitive brain surgery. The improvement of technology and machine learning can …

Brain tumor classification is an important problem in computer-aided diagnosis (CAD) for
medical applications. This paper focuses on a 3-class classification problem to differentiate …