Title :
Colon Segmentation for Prepless Virtual Colonoscopy
Author :
Taimouri, Vahid ; Liu, Xin ; Lai, Zhaoqiang ; Liu, Chang ; Pai, Darshan ; Hua, Jing
Author_Institution :
Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
Abstract :
A novel segmentation framework for a prepless virtual colonoscopy (VC) is presented, which reduces the necessity for colon cleansing before the CT scan. The patient is injected rectally with a water-soluble iodinated contrast medium using manual insufflators and a small rectal catheter. Compared to the air-based contrast medium, this technique can better preserve the color lumen and reduce the partial volume effect. However, the contrast medium, together with the fecal materials and air, makes colon wall segmentation challenging. Our solution makes no assumptions about the shape, size, and location of the fecal material in the colon. This generality allows us to label the fecal material accurately and extract the colon wall reliably. The accuracy of our technique has been verified on 60 human subjects. Compared with current VC technologies, our method is shown to be better in terms of both sensitivity and specificity. Further, in our experiments, the accuracy of the technique was comparable to that of optical colonoscopy results.
Keywords :
biological organs; biomedical materials; catheters; computerised tomography; image segmentation; medical image processing; CT scan; colon segmentation; color lumen; fecal material; manual insufflators; partial volume effect reduction; prepless virtual colonoscopy; rectal catheter; segmentation framework; water soluble iodinated contrast medium; Biological tissues; Bones; Colon; Computed tomography; Sensitivity; Three dimensional displays; Virtual colonoscopy; CT colonography (CTC); Colon segmentation; electronic colon cleansing (ECC); Algorithms; Colon; Colonoscopy; Contrast Media; Humans; User-Computer Interface;
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
DOI :
10.1109/TITB.2011.2155664