Threats and Vulnerabilities in Social Media: A Review of Cyber Security Perspectives
Saurabh Shandilya, Sachin Jain, Gaurav Sharma, Devendar Nath Pathak, S.K. Singhal, Priyanka Sharma · Advances in intelligent systems research/Advances in Intelligent Systems Research · 2025
Brain tumors are a severe medical problem due to their high mortality rate, necessitating improved diagnostic and therapeutic procedures.Radiologists must manually segment patients, which is expensive, time-consuming, and prone to error.Deep learning-based automated segmentation has recently demonstrated the potential to address these challenges, especially in the areas of image segmentation and classification.Brain tumor segmentation is essential in medical imaging to evaluate the size, location, and shape of tumors.This paper starts with an overview of multi-modal brain tumor segmentation techniques.After that, it reviews pertinent literature to evaluate how deep learning and machine learning are applied in diverse modalities.In addition, the review offers an overview of federated learning strategies that enhance global segmentation efficiency while maintaining data privacy.Lastly, the paper assesses the level of multi-modal brain tumor segmentation algorithms at the moment and looks ahead to potential developments in this area.