Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …

In computer vision, traditional machine learning (TML) and deep learning (DL) methods
have significantly contributed to the advancements of medical image analysis (MIA) by …

Multiclass classification of brain tumors is an important area of research in the field of
medical imaging. Since accuracy is crucial in the classification, a number of techniques are …

In the last decade, there has been a significant increase in medical cases involving brain
tumors. Brain tumor is the tenth most common type of tumor, affecting millions of people …

The aim of this work is to develop a Computer-Aided-Brain-Diagnosis (CABD) system that
can determine if a brain scan shows signs of Alzheimer's disease. The method utilizes …

Examination of the brain's condition with the Electroencephalogram (EEG) can be helpful to
predict abnormality and cerebral activities. The purpose of this study was to develop an …

Tumor in brain is a major cause of death in human beings. If not treated properly and timely,
there is a high chance of it to become malignant. Therefore, brain tumor detection at an …

The classification of tumours into benign and malignant continues to date to be a very
relevant and significant research topic in the cancer research domain. With the advent of …

To overcome the problems of automated brain tumor classification, a novel approach is
proposed based on long short-term memory (LSTM) model using magnetic resonance …

Medical image analysis and disease diagnosis have significantly improved with the use of AI
and Machine Learning algorithms. Automated systems for medical image analysis will help …