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Automatic segmentation of occluded vasculature via pulsatile motion analysis in endoscopic robot-assisted partial nephrectomy video

机译：内窥镜机器人辅助部分肾切除术中通过脉动分析自动分割阻塞的血管

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摘要

Hilar dissection is an important and delicate stage in partial nephrectomy, during which surgeons remove connective tissue surrounding renal vasculature. Serious complications arise when the occluded blood vessels, concealed by fat, are missed in the endoscopic view and as a result are not appropriately clamped. Such complications may include catastrophic blood loss from internal bleeding and associated occlusion of the surgical view during the excision of the cancerous mass (due to heavy bleeding), both of which may compromise the visibility of surgical margins or even result in a conversion from a minimally invasive to an open intervention. To aid in vessel discovery, we propose a novel automatic method to segment occluded vasculature from labeling minute pulsatile motion that is otherwise imperceptible with the naked eye. Our segmentation technique extracts subtle tissue motions using a technique adapted from phase-based video magnification, in which we measure motion from periodic changes in local phase information albeit for labeling rather than magnification. Based on measuring local phase through spatial decomposition of each frame of the endoscopic video using complex wavelet pairs, our approach assigns segmentation labels by detecting regions exhibiting temporal local phase changes matching the heart rate. We demonstrate how our technique is a practical solution for time-critical surgical applications by presenting quantitative and qualitative performance evaluations of our vessel detection algorithms with a retrospective study of fifteen clinical robot-assisted partial nephrectomies. (C) 2015 Elsevier B.V. All rights reserved.
机译：肺门淋巴结清扫术是部分肾切除术中重要而微妙的阶段，在此阶段，外科医生会去除肾血管周围的结缔组织。当在内窥镜视图中漏掉被脂肪掩盖的闭塞血管时，会导致严重的并发症，并因此导致不适当地夹紧。此类并发症可能包括因内部出血而导致的严重失血，以及在切除癌性肿块期间（由于大量出血）导致的手术视野的相关闭塞，这两种情况都可能损害手术切缘的可见性，甚至导致从最小的转换侵入性开放干预。为了帮助发现血管，我们提出了一种新颖的自动方法，可以通过标记肉眼无法察觉的微小脉动运动来分割阻塞的脉管系统。我们的分割技术使用基于相位的视频放大倍率的技术来提取微妙的组织运动，在这种技术中，我们根据局部相位信息的周期性变化来测量运动，尽管该过程用于标记而非放大。基于通过使用复杂小波对通过对内窥镜视频的每个帧进行空间分解来测量局部相位的方法，我们的方法通过检测表现出与心率匹配的局部时间局部相位变化的区域来分配分段标签。我们通过对十五种临床机器人辅助部分肾切除术的回顾性研究，对我们的血管检测算法进行定量和定性的性能评估，来证明我们的技术对于时间紧迫的外科手术应用是一种实用的解决方案。 （C）2015 Elsevier B.V.保留所有权利。

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