Table 6 Summary of relevant studies involving tuberculosis classification for comparative analysis
From: Explainable deep-neural-network supported scheme for tuberculosis detection from chest radiographs
Author | Methodology | Performance Scores |
|---|---|---|
Liu et al. [14] | Convolution Neural Network | Acc: 85.68% |
Liu and Huang [15] | Convolution Neural Network | Acc: 0.835 |
Rahman et al. [6] | Combinational of pre-trained CNN architecture | Acc: 96.47% (unsegmented radiographs) |
Tasci et al. [19] | InceptionV3 and Xception CNN | Acc: 97.5% (MC Dataset) |
Proposed work | Shallow-CNN | Acc: 95% |