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 …

A brain tumor is an abnormal mass of tissue located inside the skull. In addition to putting
pressure on the healthy parts of the brain, it can lead to significant health problems …

In computer vision and medical image processing, object recognition is the primary concern
today. Humans require only a few milliseconds for object recognition and visual stimulation …

Detecting brain tumors plays an important role in patients' lives as it can help specialists
save them or let them succumb to a terminal illness otherwise. Magnetic Resonance …

Healthcare system is undergoing a significant transformation from a traditional hospital-
centered to an individual-centered one, as a result of escalating chronic diseases, ageing …

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

Conventional medical imaging and machine learning techniques are not perfect enough to
correctly segment the brain tumor in MRI as the proper identification and segmentation of …

Multiparametric magnetic resonance imaging (mpMRI) is an indispensable tool in the
clinical workflow for the diagnosis and treatment planning of various diseases. Machine …

Quantum dots (QDs) are a novel kind of nanomaterial and have long piqued scientific
curiosity. As a result of their nanoscale size, they exhibit a variety of chemical and physical …

A significant issue in computer-aided diagnosis (CAD) for medical applications is brain
tumor classification. Radiologists could reliably detect tumors using machine learning …