A survey of the identification strategies of brain tumors for MR images - et. al., Ayushi Sharma, (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
A substantial rise in medical cases associated with brain tumor has been seen in recent years, making it the 10th most common type of tumor Impacting both children and adults. Due to the rising refining of medical picture technologies, Brain Tumor [BT] and their study are of considerable concern Medical image processing concepts have been used successfully in diagnosis of Tumor. For its non-invasive imaging properties, science is more oriented toward MR. Diagnosis or identification mechanisms assisted by computers have become problematic and are still an Open concern due to heterogeneity in tumor shapes, locations, and sizes. Many experts in medical field have carried out notable study work on automated detection of tumor strategies based on segmentation, grouping and variations of automatic brain tumor detection. Different brain tumor identification methods for MR images are analysed in the manuscript, including the assets and challenges found with all techniques to detect different forms of BT. The survey presented here is aimed at supporting the researchers identify the important features of types of brain tumor and identify different segmentation/classification approaches that are effective in identifying a variety of tumor types of disorders of the brain. The manuscript covers the most important approaches, procedures and operating practices. Brain tumor identification rules, priorities, restrictions, and their potential snags on MR picture.