Effective colonoscopic screening for polyps with optical or virtual means requires adequate visualization of the entire colon surface. The purpose of this study is to investigate by simulation the degree of colon surface coverage during a routine optical colonoscopy (OC). To simulate OC, a generic wide angle and fisheye camera model is used to calibrate the fisheye lens of an Olympus endoscope with a field of view of 140 degrees. Then, the colonoscopy procedure is simulated using volume rendering fly-through along the hugging corner path in the retrograde direction. This shortest path is computed using the segmented and cleansed colon CT datasets. A large number of virtual fisheye cameras are placed along the shortest path to simulate the OC. At each camera position, a discrete volumetric ray-casting method is used to determine which triangles can be seen from the camera. Then, the percentage of the covered colon surface of the OC simulation is computed. Surface coverage at this point may serve as a rough estimate of readily visualized mucosa in a standard OC examination. We also compute the percentage of the covered colon surface for the virtual colonoscopy (VC) by placing virtual pinhole cameras on the central path of the colon and flying in only the antegrade direction as well as flying in both antegrade and retrograde directions. Our simulation study reveals that about 23% of the colon surface is missed in the standard OC examination and about 9% of the colon surface is missed in the VC examination when navigating in both directions.
Structured-light rangefinder is distinguished from other range scanning systems by its use of off-the-shelf hardware and fast data acquisition. We propose a novel approach to calibrate such a system, namely, calibrate the camera and the projector of the system. This approach handles all types of distortions and produces results in high accuracy. Basically, camera calibration techniques compute the pixel-ray correspondences and represent them by a mathematic model with limited number of parameters. These parametric models, however, cannot model general distortions while distortions not modelled, sometimes, can greatly affect the quality of further applications. The proposed approach computes and maintains a ray database for all pixels explicitly. By trading memory for accuracy, this approach solves the above problem. The resulting ray database can be directly used for 3D point reconstruction using calibration system. It is also useful for model fitting and other operations.