Abstract:
In the machine learning (ML) field, the deep learning (DL) computing paradigm has recently been recognized the Benchmark. Furthermore, it has steadily become the most extensively utilized computational approach in the field of ML, generating amazing results on a variety of complex cognitive tasks, matching or even surpassing human performance in several cases. The World Health Organization (WHO) defines correct brain tumours diagnosis as the detection, identification, and categorization of the tumours based on malignancy, grade, and type. This research into the use of Magnetic Resonance Imaging (MRI) to diagnose brain cancers entails finding the tumours. The multi-task classification based on Convolutional Neural Networks (CNN) is capable of classifying and detecting tumours. By segmenting the brain tumours, a CNN-based model can also be used to identify the location of the tumours. The proposed approach outperforms other recent studies in the literature, according to the experimentation results. Furthermore, this study will support doctors and clinicians in their efforts to diagnose brain tumours condition automatically and patients will also be able to check their MRI scans
