Over the last few years, brain tumor-related clinical cases have increased substantially,
particularly in adults, due to environmental and genetic factors. If they are unidentified in the …

The brain is a complex organ and Magnetic Resonance Imaging (MRI) is the most widely
used imaging modality for diagnosing brain diseases due to its superior soft tissue contrast …

Efficient detection and classification of brain tumors using magnetic resonance images
provide significant support to the neurologists. However, many approaches developed for …

Background This paper aims to perform an examination and statistical analysis of deep
learning (DL) models utilized in the segmentation of brain tumor MR Images. Methods The …

Purpose The purpose of this study is to develop accurate and automated detection and
segmentation methods for brain tumors, given their significant fatality rates, with aggressive …

Glioma is the most prevalent type of primary brain tumor in adults. The use of artificial
intelligence (AI) in glioma is increasing and has exhibited promising results. The present …

Automated brain tumor classification is an intensively investigated problem, which recently
attracted significant attention. Convolutional neural networks (CNN) and deep learning …

Brain tumors can develop at any location of the brain with uneven boundaries and shapes.
Typically, they were increasing rapidly due to which its size approximately doubles just in …

Brain tumors are generated due to irregular development of brain cells. The life spans of the
tumor-affected individual are complex to predict as they appear in different structures and …

The segmentation of medical images is becoming increasingly important in the daily clinical
practice, particularly with regard to tumor segmentation. Artificial intelligence, which is …