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

翻译：本文展示了适当的图像预处理如何改进基于深度学习的结肠部位三维重建。假设前提是，在结肠镜检查中，应优先校正局部欠曝光和过曝光问题，而非进行全局图像光照校正。首先概述了包含图像曝光校正和RNN-SLAM的处理流程。随后，本文量化了在有无适当光照校正条件下，结肠内窥镜轨迹的重建精度。