Realistic colon simulations do not exist but would be valuable for CT colonography (CTC) CAD development and
validation of new colon image processing algorithms. The human colon is a convoluted tubular structure and very hard
to model physically and electronically. In this investigation, we propose a novel approach to generate realistic colon
simulation using mesh skinning. The method proceeds as follows. First, a digital phantom of a cylindrical tube is
modeled to simulate a straightened colon. Second, haustral folds and teniae coli are added to the cylindrical tube. Third,
a centerline equipped with rotation-minimizing frames (RMF) and distention values is computed. Fourth, mesh skinning
is applied to warp the tube around the centerline and generate realistic colon simulation. Lastly, colonic polyps in the
shape of ellipsoids are also modeled. Results show that the simulated colon highly resembles the real colon. This is the
first colon simulation that incorporates most colon characteristics in one model, including curved centerline, variable
distention, haustral folds, teniae coli and colonic polyps.
Virtual colonoscopy (VC) has gained popularity as a new colon diagnostic method over the last decade. VC is a new,
less invasive alternative to the usually practiced optical colonoscopy for colorectal polyp and cancer screening, the
second major cause of cancer related deaths in industrial nations. Haustral (colonic) folds serve as important landmarks
for virtual endoscopic navigation in the existing computer-aided-diagnosis (CAD) system. In this paper, we propose and
compare two different methods of haustral fold detection from volumetric computed tomographic virtual colonoscopy
images. The colon lumen is segmented from the input using modified region growing and fuzzy connectedness. The first
method for fold detection uses a level set that evolves on a mesh representation of the colon surface. The colon surface is
obtained from the segmented colon lumen using the Marching Cubes algorithm. The second method for fold detection,
based on a combination of heat diffusion and fuzzy c-means algorithm, is employed on the segmented colon volume.
Folds obtained on the colon volume using this method are then transferred to the corresponding colon surface. After
experimentation with different datasets, results are found to be promising. The results also demonstrate that the first
method has a tendency of slight under-segmentation while the second method tends to slightly over-segment the folds.
Conference Committee Involvement (2)
Geospatial Informatics, and Motion Imagery Analytics VIII
16 April 2018 | Orlando, FL, United States
Geospatial Informatics, Motion Imagery, and Network Analytics VII
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