  Since the development of capsule endoscopcy technology, substantial progress
were made in converting passive capsule endoscopes to robotic active capsule
endoscopes which can be controlled by the doctor. However, robotic capsule
endoscopy still has some challenges. In particular, the use of such devices to
generate a precise and globally consistent three-dimensional (3D) map of the
entire inner organ remains an unsolved problem. Such global 3D maps of inner
organs would help doctors to detect the location and size of diseased areas
more accurately, precisely, and intuitively, thus permitting more accurate and
intuitive diagnoses. The proposed 3D reconstruction system is built in a
modular fashion including preprocessing, frame stitching, and shading-based 3D
reconstruction modules. We propose an efficient scheme to automatically select
the key frames out of the huge quantity of raw endoscopic images. Together with
a bundle fusion approach that aligns all the selected key frames jointly in a
globally consistent way, a significant improvement of the mosaic and 3D map
accuracy was reached. To the best of our knowledge, this framework is the first
complete pipeline for an endoscopic capsule robot based 3D map reconstruction
containing all of the necessary steps for a reliable and accurate endoscopic 3D
map. For the qualitative evaluations, a real pig stomach is employed. Moreover,
for the first time in literature, a detailed and comprehensive quantitative
analysis of each proposed pipeline modules is performed using a non-rigid
esophagus gastro duodenoscopy simulator, four different endoscopic cameras, a
magnetically activated soft capsule robot (MASCE), a sub-millimeter precise
optical motion tracker and a fine-scale 3D optical scanner.
