Optical coherence tomography (OCT) is a non-invasive volumetric imaging modality with high spatial and temporal resolution. For imaging larger tissue structures, OCT probes need to be moved to scan the respective area. For handheld scanning, stitching of the acquired OCT volumes requires overlap to register the images. For robotic scanning and stitching, a typical approach is to restrict the motion to translations, as this avoids a full hand-eye calibration, which is complicated by the small field of view of most OCT probes. However, stitching by registration or by translational scanning are limited when curved tissue surfaces need to be scanned. We propose a marker for full six-dimensional hand-eye calibration of a robot mounted OCT probe. We show that the calibration results in highly repeatable estimates of the transformation. Moreover, we evaluate robotic scanning of two phantom surfaces to demonstrate that the proposed calibration allows for consistent scanning of large, curved tissue surfaces. As the proposed approach is not relying on image registration, it does not suffer from a potential accumulation of errors along a scan path. We also illustrate the improvement compared to conventional 3D-translational robotic scanning.

翻译：光学相干断层扫描（OCT）是一种具有高空间和时间分辨率的非侵入性体积成像模态。为了对更大范围的组织结构进行成像，OCT探针需要移动以扫描相应区域。在手持扫描中，拼接所获取的OCT体积需要重叠区域以配准图像。在机器人扫描和拼接中，通常的方法是将运动限制为平移，因为这样可以避免完整的手眼标定——而这一标定因大多数OCT探针视野较小而变得复杂。然而，当需要扫描弯曲的组织表面时，基于配准的拼接或平移扫描存在局限性。我们提出了一种标定物，用于实现机器人搭载OCT探针的全六维手眼标定。结果表明，该标定能够产生高度可重复的变换估计。此外，我们评估了对两个仿体表面的机器人扫描，以证明所提出的标定方法能够实现对大范围弯曲组织表面的一致性扫描。由于该方法不依赖图像配准，因此不会沿扫描路径出现潜在误差累积。我们还展示了该方法相较于传统三维平移机器人扫描的性能提升。