  As the number of people affected by diseases in the gastrointestinal system
is ever-increasing, a higher demand on preventive screening is inevitable. This
will significantly increase the workload on gastroenterologists. To help reduce
the workload, tools from computer vision may be helpful. In this paper, we
investigate the possibility of constructing 3D models of whole sections of the
human colon using image sequences from wireless capsule endoscope video,
providing enhanced viewing for gastroenterologists. As capsule endoscope images
contain distortion and artifacts non-ideal for many 3D reconstruction
algorithms, the problem is challenging. However, recent developments of virtual
graphics-based models of the human gastrointestinal system, where distortion
and artifacts can be enabled or disabled, makes it possible to ``dissect'' the
problem. The graphical model also provides a ground truth, enabling computation
of geometric distortion introduced by the 3D reconstruction method. In this
paper, most distortions and artifacts are left out to determine if it is
feasible to reconstruct whole sections of the human gastrointestinal system by
existing methods. We demonstrate that 3D reconstruction is possible using
simultaneous localization and mapping. Further, to reconstruct the
gastrointestinal wall surface from resulting point clouds, varying greatly in
density, Poisson surface reconstruction is a good option. The results are
promising, encouraging further research on this problem.
