Affine-invariant anisotropic detector for soft tissue tracking in minimally invasive surgery
Affine-invariant anisotropic detector for soft tissue tracking in minimally invasive surgery
复制标题
DOI：
10.1109/isbi.2009.5193238
复制
发表时间：
2009-06
期刊：
影响因子：
--
通讯作者：
S. Giannarou;M. V. Scarzanella;Guang-Zhong Yang
中科院分区：
文献类型：
--
作者：
S. Giannarou;M. V. Scarzanella;Guang-Zhong Yang
在计算机辅助微创外科手术中，可靠的特征跟踪对于精确的组织变形恢复、三维解剖配准和导航非常重要。尽管在计算机视觉领域开发了广泛的特征检测器，但由于缺乏可靠的特征标志以及自由形式的组织变形和不断变化的手术场景的截然不同的视觉外观，这些方法在手术导航中的直接应用表现出了巨大的困难。本文的目的是引入一种基于各向异性特征的仿射不变特征检测器，以确保可靠和持久的特征跟踪。提出了一种新的基于各向异性模式强度的尺度自适应表示，而仿射自适应依赖于其固有的傅立叶特性，并基于二阶矩矩阵进行了有效的空间实现。将所提出的检测器与当前最先进的特征检测器进行比较，并使用从机器人辅助的微创外科手术中记录的在体视频序列来评估它们各自的性能。
Reliable feature tracking is important for accurate tissue deformation recovery, 3D anatomical registration and navigation in computer assisted minimally invasive surgical procedures. Despite a wide range of feature detectors developed in the computer vision community, direct application of these approaches to surgical navigation has shown significant difficulties due to the paucity of reliable feature landmarks coupled with free-form tissue deformation and contrastingly different visual appearances of changing surgical scenes. The purpose of this paper is to introduce an affine-invariant feature detector based on anisotropic features to ensure reliable and persistent feature tracking. A novel scale-space representation is proposed for scale adaptation based on the strength of the anisotropic pattern whereas affine adaptation relies on its intrinsic Fourier properties with an efficient spatial implementation based on the second moment matrix. The proposed detector is compared against the current state-of-the-art feature detectors and their respective performance is evaluated with in vivo video sequences recorded from robotic assisted minimally invasive surgical procedures.