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:本研究表明适当的影像预处理可以改善基于深度学习的结肠部位三维重建。对于内窥镜检查而言,我们假设应该矫正局部的低曝光和高曝光,而非全局影像照明校正。首先给出了包括影像曝光校正和RNN-SLAM的流水线的概述。然后,在有适当照明校正和无照明校正的情况下,本文量化了结肠内窥镜轨迹的重建精度。