照明增强有助于重建结肠镜表面
Lighting Enhancement Aids Reconstruction of Colonoscopic Surfaces
摘要：
结肠镜检查期间的高筛查覆盖率对于有效预防结肠癌至关重要。以前的工作已经允许通过实时从结肠镜视频重建3D结肠镜表面来提醒医生未调查的区域。然而，结肠镜检查视频的照明不一致可能导致结肠镜重建系统的关键组件SLAM优化失败。在这项工作中，我们专注于结肠镜检查视频中的照明问题。为了成功地提高结肠镜检查视频的照明一致性，我们发现有必要进行照明校正，以适应最近的视频帧的强度分布。为了实时实现这一点，我们设计并训练了一个RNN网络。该网络在伽马校正过程中调整伽马值。应用于结肠镜表面重建系统中，我们的轻量级模型显着提高了重建成功率，使结肠镜视频片段的更大比例的可重建，并提高已重建片段的重建质量。
英文摘要：
High screening coverage during colonoscopy is crucial to effectively prevent colon cancer. Previous work has allowed alerting the doctor to unsurveyed regions by reconstructing the 3D colonoscopic surface from colonoscopy videos in real-time. However, the lighting inconsistency of colonoscopy videos can cause a key component of the colonoscopic reconstruction system, the SLAM optimization, to fail. In this work we focus on the lighting problem in colonoscopy videos. To successfully improve the lighting consistency of colonoscopy videos, we have found necessary a lighting correction that adapts to the intensity distribution of recent video frames. To achieve this in real-time, we have designed and trained an RNN network. This network adapts the gamma value in a gamma-correction process. Applied in the colonoscopic surface reconstruction system, our light-weight model significantly boosts the reconstruction success rate, making a larger proportion of colonoscopy video segments reconstructable and improving the reconstruction quality of the already reconstructed segments.
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