The difficulty or cost of obtaining data or labels in applications like medical imaging has
progressed less quickly. If deep learning techniques can be implemented reliably …

Magnetic Resonance Imaging (MRI) is a principal diagnostic approach used in the field of
radiology to create images of the anatomical and physiological structure of patients. MRI is …

Accurate and precise brain tumor MR images classification plays important role in clinical
diagnosis and decision making for patient treatment. The key challenge in MR images …

Brain tumors present a significant medical challenge, demanding accurate and timely
diagnosis for effective treatment planning. These tumors disrupt normal brain functions in …

With the advancement in technology, machine learning can be applied to diagnose the
mass/tumor in the brain using magnetic resonance imaging (MRI). This work proposes a …

OBJECTIVE Magnetic resonance imaging (MRI) offers high-resolution anatomical images
for diagnosing brain tumors. This study aims to improve classification accuracy and …

Brain tumors represent one of the most challenging tumors that affect the human body due to
the nonlinear characteristics of their morphological and textural appearance. Automated …

Brain tumors are a critical public health concern, often resulting in limited life expectancy for
patients. Accurate diagnosis of brain tumors is crucial to develop effective treatment …

Background: Automatic classification of brain tumors is an important issue in computeraided
diagnosis (CAD) for medical applications since it can efficiently improve the clinician's …

This paper investigates the use of transfer learning in MRI-based brain tumor detection. The
goal is to develop a reliable and efficient model for accurately classifying brain tumors …