Computer-aided diagnostic (CAD) systems use machine learning methods that provide a
synergistic effect between the neuroradiologist and the computer, enabling an efficient and …

In recent decades, human brain tumor detection has become one of the most challenging
issues in medical science. In this paper, we propose a model that includes the template …

Deep Learning is the newest and the current trend of the machine learning field that paid a
lot of the researchers' attention in the recent few years. As a proven powerful machine …

The eagle expresses of cloud computing plays a pivotal role in the development of
technology. The aim is to solve in such a way that it will provide an optimized solution. The …

Biopsies are used to classify brain tumors and are not routinely performed prior to definitive
brain surgery. Radiologists may be able to detect tumors with fewer invasive procedures if …

The eagle expresses of cloud computing plays a pivotal role in the development of
technology. The technology momentum is gaining cloud system environment across the …

Objectives: In this paper, we look at how to design and build a system to find tumors using 2
Convolutional Neural Network (CNN) models. With the help of digital image processing and …

Magnetic Resonance Imaging (MRI) is a noninvasive technique used in medical imaging to
diagnose a variety of disorders. The majority of previous systems performed well on MRI …

Deep Learning is the newest and the current trend of the machine learning field that paid a
lot of the researchers' attention in the recent few years. As a proven powerful machine …

Brain tumour is an abnormal growth of living cells within the brain. This mass of tumour
grows within the skull, and due to which, normal brain activity is affected. If brain tumour is …