Purpose

In surgical oncology, complete cancer resection and lymph node identification are challenging due to the lack of reliable intraoperative visualization. Recently, endoscopic radio-guided cancer resection has been introduced where a novel tethered laparoscopic gamma detector can be used to determine the location of tracer activity, which can complement preoperative nuclear imaging data and endoscopic imaging. However, these probes do not clearly indicate where on the tissue surface the activity originates, making localization of pathological sites difficult and increasing the mental workload of the surgeons. Therefore, a robust real-time gamma probe tracking system integrated with augmented reality is proposed.

Methods

A dual-pattern marker has been attached to the gamma probe, which combines chessboard vertices and circular dots for higher detection accuracy. Both patterns are detected simultaneously based on blob detection and the pixel intensity-based vertices detector and used to estimate the pose of the probe. Temporal information is incorporated into the framework to reduce tracking failure. Furthermore, we utilized the 3D point cloud generated from structure from motion to find the intersection between the probe axis and the tissue surface. When presented as an augmented image, this can provide visual feedback to the surgeons.

Results

The method has been validated with ground truth probe pose data generated using the OptiTrack system. When detecting the orientation of the pose using circular dots and chessboard dots alone, the mean error obtained is \(0.05^{\circ }\) and \(0.06^{\circ }\), respectively. As for the translation, the mean error for each pattern is 1.78 mm and 1.81 mm. The detection limits for pitch, roll and yaw are \(360^{\circ }, 360^{\circ }\) and \(8^{\circ }\)–\(82^{\circ }\cup 188^{\circ }\)–\(352^{\circ }\) .

Conclusion

The performance evaluation results show that this dual-pattern marker can provide high detection rates, as well as more accurate pose estimation and a larger workspace than the previously proposed hybrid markers. The augmented reality will be used to provide visual feedback to the surgeons on the location of the affected lymph nodes or tumor.

中文翻译：

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系留腹腔镜伽马探头的传感区域的跟踪和可视化。

目的

在外科肿瘤学中，由于缺乏可靠的术中可视化，完整的癌症切除和淋巴结识别具有挑战性。最近，引入了内窥镜放射引导的癌症切除术，其中一种新型系留腹腔镜伽马探测器可用于确定示踪剂活动的位置，这可以补充术前核成像数据和内窥镜成像。然而，这些探针不能清楚地指示活动起源于组织表面的哪个位置，使得病理部位的定位变得困难并增加了外科医生的脑力工作量。因此，提出了一种与增强现实集成的鲁棒实时伽马探测器跟踪系统。

方法

伽马探针上附加了双模式标记，它结合了棋盘顶点和圆点，以提高检测精度。基于斑点检测和基于像素强度的顶点检测器同时检测两种模式，并用于估计探针的姿态。将时间信息纳入框架以减少跟踪失败。此外，我们利用从运动中的结构生成的 3D 点云来找到探针轴和组织表面之间的交点。当呈现为增强图像时，这可以为外科医生提供视觉反馈。

结果

该方法已通过使用 OptiTrack 系统生成的地面实况探针姿态数据进行了验证。当单独使用圆点和棋盘点检测姿势的方向时，获得的平均误差分别为\(0.05^{\circ }\)和\(0.06^{\circ }\)。至于平移，每个图案的平均误差为 1.78 毫米和 1.81 毫米。俯仰、滚转和偏航的检测限为\(360^{\circ }, 360^{\circ }\)和\(8^{\circ }\) – \(82^{\circ }\cup 188 ^{\circ }\) – \(352^{\circ }\)。

结论

性能评估结果表明，与之前提出的混合标记相比，这种双模式标记可以提供更高的检测率，以及更准确的姿态估计和更大的工作空间。增强现实将用于向外科医生提供有关受影响淋巴结或肿瘤位置的视觉反馈。