Artificial Intelligence and Communication Technologies
Automatic Brain Tumor Detection: A Review
Authors: Mohit Srivastava and Manjeet Singh
Publishing Date: 15-09-2022
ISBN: 978-81-955020-5-9
Abstract
Brain tumor is a deadly disease and its detection and diagnosis is a primary concern. Human-assisted manual classification results in inaccurate prediction and identification can result from hence we employ computer-aided technology to aid with diagnosis accuracy. Numerous challenges like its position in the brain, tumor type, abnormality of cells, image segmentation, etc. are needed for its cure. After segmentation of MRI images, on the basis of variation found in tumor tissue characteristics, the tumor is mainly divided into 2 categories i.e. malignant and benign. Numerous reviews on Brain Tumor segmentation is presented to simplify and help the researchers working in this field. This research also accentuates the advantage and drawbacks of earlier proposed classification techniques. Different types of tumors, their stages, and numerous techniques carried out in the detection of brain tumor using neural networks are also discussed. Diverse methods and the methodologies presented in this analysis will be advantageous for scholars researching in this domain.
Keywords
Brain tumor, MRI, Datasets, Deep Learning, Filter, Segmentation, ML, CNN
Cite as
Mohit Srivastava and Manjeet Singh, "Automatic Brain Tumor Detection: A Review", In: Saroj Hiranwal and Garima Mathur (eds), Artificial Intelligence and Communication Technologies, SCRS, India, 2022, pp. 319-329. https://doi.org/10.52458/978-81-955020-5-9-32