Modern computer vision algorithms are based on convolutional neural networks (CNNs),
and both end-to-end learning and transfer learning modes have been used with CNN for …

Brain diseases are considered life-threatening malignant diseases. Malignant brain
diseases, such as glioblastoma multiforme (GBM) and metastatic brain tumours, present …

Purpose This study aims to perform a comprehensive systematic review of deep learning
(DL) models in predicting RT-induced toxicity. Materials and methods A literature review was …

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

Simple Summary This study presents a hybrid model for brain tumor detection. Contrary to
manual featur extraction, features extracted from a convolutional neural network are used to …

Deep learning has developed into a very active and practical research tool that is applied in
many domains of image processing. Pre-processing is an enhancement of the picture data …

As a result of the speed and availability of the Internet, mobile devices and apps are in
widespread usage throughout the world. Thus, they can be seen in the hands of nearly …

Cancer of the brain is most common in the elderly and young and can be fatal in both. Brain
tumours can heal better if they are diagnosed and treated quickly. When it comes to …

Magnetic resonance imaging (MRI) plays an important role in disease diagnosis. The noise
that appears in MRI images is commonly governed by a Rician distribution. The bendlets …

The brain is the most vital component of the neurological system. Therefore, brain tumor
classification is a very challenging task in the field of medical image analysis. There has …