Convolutional neural networks (CNNs) constitute a widely used deep learning approach that
has frequently been applied to the problem of brain tumor diagnosis. Such techniques still …

Creating machines that behave and work in a way similar to humans is the objective of
artificial intelligence (AI). In addition to pattern recognition, planning, and problem-solving …

The study of neuroimaging is a very important tool in the diagnosis of central nervous system
tumors. This paper presents the evaluation of seven deep convolutional neural network …

Anomaly detection in medical imaging, particularly within the realm of magnetic resonance
imaging (MRI), stands as a vital area of research with far‐reaching implications across …

Brain tumor detection in the initial stage is becoming an intricate task for clinicians
worldwide. The diagnosis of brain tumor patients is rigorous in the later stages, which is a …

Brain tumors significantly impact human health due to their complexity and the challenges in
early detection and treatment. Accurate diagnosis is crucial for effective intervention, but …

Most primary brain malignancies are malignant tumors characterized by masses of
abnormal tissue that grow uncontrollably. Recently, deep transfer learning (DTL) has been …

The accurate and rapid detection of brain tumors is crucial for expediting patient
rehabilitation and saving lives. Brain tumors exhibit considerable variation in size, shape …

A significant topic of investigation in the area of medical imaging is brain tumor classification.
Since precision is significant for classification, computer vision researchers have developed …

The use of MRI analysis for BTD and tumor type detection has considerable importance
within the domain of machine vision. Numerous methodologies have been proposed to …