1 Introduction  
1.1 Brain Tumors and Their Types  
1.2 Brain Imaging Modalities  

2 Challenges in Medical Image Analysis  

3 Glioma Brain Tumor Segmentation  

4 Segmentation Methods using Handcrafted Features  
4.1 Random Field Based Methods  
4.2 Atlas Based Methods  
4.3 Expectation Maximization Based Methods  
4.4 Clustering Based Methods  
4.5 Random Forest Based Methods  
4.6 Neural Network Based Methods  

5 Deep Neural Network  
5.1 Evolution of DNN  
5.2 Handling Class Imbalance Problem  
5.4 Hardware and Software for DNN  
5.5 Proposed Architecture for Tumor Segmentation  

6 Limitations of Tumor Segmentation and Overall Survival Prediction  

7 Conclusion and Future Research Directions