A Novel Medical Image Quality Index

Abstract

A novel medical image quality index using grey relational coefficient calculation is proposed in this study. Three medical modalities, DR, CT and MRI, using 30 or 60 images with a total of 120 images used for experimentation. These images were first compressed at ten different compression ratios (10 ∼ 100) using a medical image compression algorithm named JJ2000. Following that, the quality of the reconstructed images was evaluated using the grey relational coefficient calculation. The results were shown consistent with popular objective quality metrics. The impact of different image aspects on four grey relational coefficient methods were further tested. The results showed that these grey relational coefficients have different slopes but very high consistency for various image areas. Nagai's grey relational coefficient was chosen in this study because of higher calculation speed and sensitivity. A comparison was also made between this method and other windows-based objective metrics for various window sizes. Studies found that the grey relational coefficient results are less sensitive to window size changes. The performance of this index is better than some windows-based objective metrics and can be used as an image quality index.