The first important step in pre-processing data for 3D virtual colonoscopy
requires careful segmentation of a complicated shaped colon. We describe al
l automatic colon segmentation method with a new patient-friendly bowel pre
paration scheme. This new bowel preparation makes the segmentation more app
ropriate for digitally removing undesirable remains in the colon. With the
aim of segmenting the colon accurately, we propose two techniques which can
solve the partial-volume-effect (PVE) problem on the boundaries between lo
w and high intensity regions. Based on the features of the adverse PVE voxe
ls on the gas and fluid boundary inside the colon, our vertical filter clim
inates these PVE voxels. By seriously considering the PVE on the colon boun
dary. our gradient-magnitude-based region growing algorithm improves the ac
curacy of the boundary. The result of the automatic colon segmentation meth
od is illustrated with both extracted 2D images from the experimental volum
etric abdominal CT datasets and a reconstructed 3D colon model.