Automated seed placement for colon segmentation in computed tomography colonography.
OBJECTIVE
To present an algorithm to automatically locate seeds for colon segmentation in computed tomography colonography (CTC).


METHODS
The algorithm automatically locates two points (seeds) inside the colon lumen. Because of their high distention and fixed anatomic position, we focus on the cecum and rectum for automatic seed placement. We use two-dimensional morphological operators that find pockets of colonic air of sufficient size. For the rectum, we search within an inferiorly and centrally located CT slice. For the cecum, we search in a group of CT slices in the middle of the scanned volume on the patient's right side. We applied our automated algorithm to segment the colon in 292 consecutive cases of CTC (146 prone, 146 supine).


RESULTS
After automated seed placement, 83.2% (243 of 292) of the colons were segmented completely and 9.6% (28 of 292) were segmented partially. The unsegmented colon parts were present in datasets where the colon was collapsed in more than one place or because seeds could not be placed in regions filled with fluid. In the remaining 7.2% (21 of 292) of cases, the automatic segmentation leaked outside the colon because of a limitation of the contrast-enhanced fluid detection algorithm.


CONCLUSIONS
Fully automatic seed placement for colonic segmentation is feasible in the majority of cases without seeding of undesired extracolonic air.
Iordanescu
Gheorghe
G
Department of Radiology, National Institutes of Health, Building 10, Room 1C660, 10 Center Drive MSC 1182, Bethesda, MD 20892-1182, USA.
Pickhardt
Perry J
PJ
Choi
J Richard
JR
Summers
Ronald M
RM
D000328:Adult; D000368:Aged; D000465:Algorithms; D002432:Cecum / Q000000981:diagnostic imaging; D003106:Colon / Q000000981:diagnostic imaging*; D023881:Colonography, Computed Tomographic / Q000379:methods*; D015179:Colorectal Neoplasms / Q000175:diagnosis*; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D012007:Rectum / Q000000981:diagnostic imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted