Electrical Engineering Department, Vanderbilt University, Nashville, TN 37212, USA.
IEEE Trans Biomed Eng. 2011 Jul;58(7):1985-93. doi: 10.1109/TBME.2011.2112656. Epub 2011 Feb 10.
This article presents a method designed to automatically track cortical vessels in intra-operative microscope video sequences. The main application of this method is the estimation of cortical displacement that occurs during tumor resection procedures. The method works in three steps. First, models of vessels selected in the first frame of the sequence are built. These models are then used to track vessels across frames in the video sequence. Finally, displacements estimated using the vessels are extrapolated to the entire image. The method has been tested retrospectively on images simulating large displacement, tumor resection, and partial occlusion by surgical instruments and on 21 video sequences comprising several thousand frames acquired from three patients. Qualitative results show that the method is accurate, robust to the appearance and disappearance of surgical instruments, and capable of dealing with large differences in images caused by resection. Quantitative results show a mean vessel tracking error (VTE) of 2.4 pixels (0.3 or 0.6 mm, depending on the spatial resolution of the images) and an average target registration error (TRE) of 3.3 pixels (0.4 or 0.8 mm).
本文提出了一种旨在自动跟踪手术显微镜视频序列中皮质血管的方法。该方法的主要应用是估计肿瘤切除过程中发生的皮质位移。该方法分三个步骤进行。首先,在序列的第一帧中选择血管模型。然后,使用这些模型在视频序列中的帧之间跟踪血管。最后,使用血管估计的位移外推到整个图像。该方法已在模拟大位移、肿瘤切除和手术器械部分遮挡的图像以及从三位患者采集的包含数千个帧的 21 个视频序列上进行了回顾性测试。定性结果表明,该方法准确,对手术器械的出现和消失具有鲁棒性,并且能够处理由于切除而导致的图像差异较大的问题。定量结果表明,血管跟踪误差(VTE)的平均值为 2.4 像素(取决于图像的空间分辨率,为 0.3 或 0.6 毫米),目标配准误差(TRE)的平均值为 3.3 像素(0.4 或 0.8 毫米)。