This paper proposes a robust algorithm to detect colon polyps and cancerous
lesions in virtual colonoscopy and present them to the user by automatically
guiding the virtual camera. The detection algorithm uses Gaussian filters to
construct the Hessian matrix, which represents the second order derivatives of a
vector variate scalar valued function. Based on the sign and scale of the
eigenvalues of the Hessian matrix, blob like lesions can be selected on a given
scale. In the visualization stage the camera is moved along the colon centerline
with its speed and viewing direction adopted to the results of detection. The
camera path and the viewing direction are described by Kochanek-Bartels splines.
The velocity along the path is also governed by a C^2 continuous function. The
resulting fly through is smooth and physically plausible, and it is guaranteed
that the user can see all regions of interest and spends sufficient time looking
at each of them.