Comparison Among Different “Brain Tumor Detection” Methods

EasyChair Preprint 15521

Abstract

Brain Tumor is a condition which arises due to the growth of abnormal cells which may be cancerous or non-cancerous. Early disease identification and curing strategies are important to know for a person suffering to ensure better life longevity. Radiology and diagnostics have brain tumor as its critical area that is aimed at enhancing early detection and patient outcomes. This review consolidates findings from 15-20 research studies, summarizing key advancements and comparing methods in brain tumor detection. The key techniques reviewed includes MRI-based imaging, machine learning, deep learning including neural networks, and advanced segmentation methods, each contributing to improved accuracy in detection. While significant progress has been made, challenges such as accuracy and computational requirements remain. Future research directions are proposed for enhancing detection methodologies. This paper provides a consolidated resource for researchers in the field, highlighting existing advancements and recognizing fields for upcoming analysis in detecting brain tumor

Keyphrases: Brain Tumor, CNN, Classification, MRI Scan, YOLO, deep learning, machine learning

@booklet{EasyChair:15521,
  author    = {Esha Aggarwal and Diksha Raj and Shreya Sharma and Shobha Sharma},
  title     = {Comparison Among Different “Brain Tumor Detection” Methods},
  howpublished = {EasyChair Preprint 15521},
  year      = {EasyChair, 2024}}