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 …

The automatic segmentation of brain tumors in Magnetic Resonance Imaging (MRI) plays a
major role in accurate diagnosis and treatment planning. The present study proposes a new …

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 …

Brain tumor detection depicts a tough job because of its shape, size and appearance
variations. In this manuscript, a deep learning model is deployed to predict input slices as a …

Featured Application This review provides a critical review of deep/machine learning
algorithms used in the identification of ischemic stroke and demyelinating brain diseases. It …

Lung cancer is a fatal type of cancer and it causes of severe deaths of approximately 422
people every day, worldwide. However, an early diagnosis is an expedient requirement for …

Brain tumor is a group of anomalous cells. The brain is enclosed in a more rigid skull. The
abnormal cell grows and initiates a tumor. Detection of tumor is a complicated task due to …

Human gait recognition (HGR) shows high importance in the area of video surveillance due
to remote access and security threats. HGR is a technique commonly used for the …

Recently, medical imaging and machine learning gained significant attention in the early
detection of brain tumor. Compound structure and tumor variations, such as change of size …

Several countries are most reliant on agriculture either in terms of employment opportunities,
national income, availability of a raw material, food production, to name but a few. However …