In World neurosurgery ; h5-index 47.0
Numerous scientists and researchers have been developing advanced procedures and methods for diagnosing the kind and phase of a human tumour. Brain tumours, which are neoplastic and abnormal developments of brain cells, are one of the most prominent causes of death. Brain tumours, also known as lesions or neoplasia, may be roughly classified as either primary or metastatic. Primary brain tumours arise from brain tissue and its surrounding environment. The recognition of brain tumours using magnetic resonance images (MRIs) via a deep learning technique such as Convolutional Neural Network (CNN) has garnered significant academic interest over the last few decades. In this study, a detailed evaluation based on bibliometrics is considered in order to synthesise and organise the available academic literature and to identify current research trends and hotspots. We used bibliometric methodologies and a literature review for the CNN-based Brain Tumor to synthesise and evaluate prior studies. For this bibliometric analysis, we applied the Visualization of Similarity Viewer (VOSviewer) programme to classify the major publications, notable journals, financial sponsors, and affiliations. In conclusion, we suggest that one of the next paths of study will be the incorporation of other databases to advance CNN-based brain tumour identification from MRIs.
Rath Arati, Mohanty Dipak Kumar, Prasad Mishra Bhabani Shankar, Bagal Dilip Kumar
2022-Nov-25
Brain Tumor, CNN, Deep Learning, MRI
