Deep Learning for Chest Radiographs

Chapter 10: Comparative analysis of computer-aided classification systems designed for chest radiographs: Conclusion and future scope

Abstract

This chapter concludes the present work by collectively comparing the performance of the different computer-aided classification (CAC) systems designed. It also discusses the future work that involves other convolution neural network (CNN) models, such as VGGNet and ResNet-50, and other variants, such as DarkNet and NasNet. These CNN models can be used to design similar CAC systems for the binary classification of chest radiographs as designed in the present work. These CAC systems could be designed for multiclass classification such as the three-class classification of chest radiographs into Normal, ...