Electronic cleansing in computed tomography colonography using AT layer identification with integration of gradient directional second derivative and material fraction model

Electronic cleansing in computed tomography colonography using AT layer identification with integration of gradient directional second derivative and material fraction model

BMC Medical Imaging, September 2017

28870147

Krisorn Chunhapongpipat, Ratinan Boonklurb, Bundit Chaopathomkul, Sirod Sirisup, Rajalida Lipikorn

In computed tomography colonography images, electronic cleansing (EC) is applied to remove opacified residual materials, called fecal-tagging materials (FTM), using positive-contrast tagging agents and laxative to facilitate polyp detection. The proposed EC, EC prop , integrates the gradient directional second derivative into material fraction model to preserve submerged soft tissue (ST) under FTM. Three-material fraction model is used to remove FTM and artifacts at air-tagging (AT) layers and T-junctions where air, ST, and FTM material meet simultaneously. Moreover, the proposed AT layer identification is used to distinguish AT layers from air-tissue-tagging (ATT) layers in order to preserve ATT layers during cleansing. The clinical evaluation on 467 3-Dimensional band view images was conducted by the abdominal radiologist using four grading levels of cleansing quality with five causes of low quality EC. The amount of the remaining artifacts at T-junctions was approximated from the results of EC prop . The results from EC prop were compared with the results from syngo.via Client 3.0 Software, EC syngo , and the fast three-material modeling, EC prev , using the preference of the radiologist. Two-tailed paired Wilcoxon signed rank test is used to indicate statistical significance. The average grade on cleansing quality is 2.89 out of 4. The artifacts at T-junctions from 86.94% of the test images can be removed, whereas artifacts at T-junctions from only 13.06% of the test images cannot be removed. For 13.06% of the test images, the results from EC prop are more preferable to the results from EC syngo (p<0.008). For all the test images, the results from EC prop are more preferable to the results from EC prev (p<0.001). Finally, the visual assessment shows that EC prop can preserve ATT layers, submerged polyps and folds while EC prev can preserve only submerged folds but fails to preserve ATT layers. From our implementation, EC prop can improve the performance of the existing EC, such that it can preserve ST, especially ATT layers and remove the artifacts at T-junctions which have never been proposed by any other methods before.