Image Texture Descriptors to Quantify Bilateral Filter on Low Dose Computerized Tomography

Reducing the Radiation Dose in Multi Slice Computerized Tomography MSCT/CT is a significant concern. The Non-Linear Bilateral Filter BF was proved to have the property of de-noising digital images without jeopardizing the fine structures. This paper tests the BF performance on low dose CT by using Image Texture Metrics which have not been reported in literature. Set of CT images of dedicated CT phantom were acquired at four different radiation doses by means of minimizing the X-Ray Tube Current. As radiation dose is lowered, the noise will unavoidably increase degrading the diagnostic value of the CT image. The BF was applied to achieve image space noise removal. The value of each BF parameter was changed set of times. The quantitative assessment of the amount of noise reduction was done using eight metrics based on image texture descriptors that have not been tried before. Particularly, we used three histogram moments (Variance, Skewness, Kurtosis) and five cooccurrence matrix descriptors (Correlation, Contrast, Uniformity, Homogeneity, Entropy). The results showed that these descriptors are reliable metrics to assess BF performance. Each image descriptor value -after applying BF on low dose CT imagesis enhanced toward the full dose CT image. Therefore, these metrics have provided additional proofs about the capability of BF toward enhancing the diagnostic value of the low dose MSCT. We concluded that: 1-) Texture descriptors are reliable measures similar to other metrics that are commonly used in literature, and 2-) BF can contribute to reduce X-Ray dose in routine CT. Also, the results have leaded to propose the effective procedure to employ BF on CT.