Live Tracking and Dense Reconstruction for Handheld Monocular Endoscopy
Live Tracking and Dense Reconstruction for Handheld Monocular Endoscopy
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DOI：
10.1109/tmi.2018.2856109
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发表时间：
2019-01-01
影响因子：
10.6
通讯作者：
Martinez Montiel, Jose Maria
中科院分区：
文献类型：
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作者：
Mahmoud, Nader;Collins, Toby;Martinez Montiel, Jose Maria
当代内窥镜同时定位和映射（SLAM）方法准确地计算内窥镜姿势，但是，它们只提供稀疏的3-D重建，很难描述手术场景。我们提出了一种新的密集SLAM方法，其质量是：1）单目，只需要手持单目内窥镜的RGB图像; 2）快速，提供内窥镜位置跟踪和3-D场景重建，并行线程运行; 3）密集，产生准确的密集重建; 4）鲁棒，严重的照明变化，不良的纹理和小变形，这是典型的内窥镜检查;以及5）独立的，不需要任何基准或外部跟踪装置，因此，它可以平滑地集成到手术工作流程中。它的工作原理如下。首先，使用稀疏SLAM特征匹配来估计准确的簇帧姿态。该系统根据视差标准分割视频帧的集群。接下来，密集的集群框架之间的匹配计算并行的变分方法，结合零均值归一化互相关和梯度Huber范数正则化。这种组合在现代GPU上以合理的时间预算应对具有挑战性的照明和纹理。它可以优于纯立体重建，因为帧簇可以提供来自内窥镜运动的更大视差。我们提供了一个广泛的实验验证真实的序列的猪腹腔，在体内和体外。我们还显示了对人肝脏的定性评价。此外，我们与其他密集SLAM方法进行了比较，显示了在精度，密度和计算时间方面的性能增益。
Contemporary endoscopic simultaneous localization and mapping (SLAM) methods accurately compute endoscope poses; however, they only provide a sparse 3-D reconstruction that poorly describes the surgical scene. We propose a novel dense SLAM method whose qualities are: 1) monocular, requiring only RGB images of a handheld monocular endoscope; 2) fast, providing endoscope positional tracking and 3-D scene reconstruction, running in parallel threads; 3) dense, yielding an accurate dense reconstruction; 4) robust, to the severe illumination changes, poor texture and small deformations that are typical in endoscopy; and 5) self-contained, without needing any fiducials nor external tracking devices and, therefore, it can be smoothly integrated into the surgical workflow. It works as follows. First, accurate cluster frame poses are estimated using the sparse SLAM feature matches. The system segments clusters of video frames according to parallax criteria. Next, dense matches between cluster frames are computed in parallel by a variational approach that combines zero mean normalized cross correlation and a gradient Huber norm regularizer. This combination copes with challenging lighting and textures at an affordable time budget on a modern GPU. It can outperform pure stereo reconstructions, because the frames cluster can provide larger parallax from the endoscope's motion. We provide an extensive experimental validation on real sequences of the porcine abdominal cavity, both in-vivo and ex-vivo. We also show a qualitative evaluation on human liver. In addition, we show a comparison with the other dense SLAM methods showing the performance gain in terms of accuracy, density, and computation time.