Contrast-enhanced Based on Abdominal Kernels for CT Image Noise Reduction

In the medical image applications, computed tomography (CT) images can be used for visualizing the image of abdominal (belly). It was from exposes of radiation dose in which the noise is relatively high. Contrast-enhanced is the digital manipulating carried out to increase the contrast and eliminate the noise in digital imaging. In this paper, an analysis of contrast-enhanced based on abdominal kernels in CT has been presented. Images were reconstructed consists of five kernels for CT abdomen using B20s, B31s, B35s, B41s, and B46s on CT Scan Siemens SOMATOM Emotion 16 Slice. The data were analyzed by using the signal-to-noise ratio (PSNR), root mean square error (RMSE) and maximum absolute error (MAE) which is used to compare each kernel on CT images. Therefore, the selection of the appropriate kernel can reduce noise and improve the contrast to optimize the quality of the CT images to determine the early diagnosis.