  This contribution shows how an appropriate image pre-processing can improve a
deep-learning based 3D reconstruction of colon parts. The assumption is that,
rather than global image illumination corrections, local under- and
over-exposures should be corrected in colonoscopy. An overview of the pipeline
including the image exposure correction and a RNN-SLAM is first given. Then,
this paper quantifies the reconstruction accuracy of the endoscope trajectory
in the colon with and without appropriate illumination correction
