Automatic colonic fold segmentation for computed tomography colonography

Human colon has complex structures mostly because of the haustral folds. Haustral folds are thin flat protrusions on the colon wall, which inherently attached on the colon wall. These structures may complicate the shape analysis for computer-aided detection of colonic polyps (CADpolyp); however, they can serve as solid reference during image interpretation in computed tomographic colonography (CTC). Therefore, in this study, based on a clear model of the haustral fold boundaries, we employ level set method to automatically segment the fold surfaces. We believe the segmented folds have the potential to significantly benefit various post-procedures in CTC, e.g., supine-prone registration, synchronized image interpretation, automatic polyp matching, CADpolyp, teniae coli extraction, etc. For the first time, with assistance from physician experts, we established the ground truth of haustral fold boundaries of 15 real patient data from two medical centers, based on which we evaluated our algorithm. The results demonstrated that about 92.7% of the folds are successfully detected. Furthermore, we explored the segmented area ratio (SAR), i.e., the ratio between the areas of the intersection and the union of the expert-drawn and the automatically-segmented folds, to measure the accuracy of the segmentation algorithm. The averaged result of SAR=86.2% shows a good match between the ground truth and our segmentation results.