Abstract
Navigation for thoracoabdominal puncture surgery is used to locate the needle entry point on the patient's body surface. The traditional reflective ball navigation method is difficult to position the needle entry point on the soft, irregular, smooth chest and abdomen. Due to the lack of clear characteristic points on the body surface using structured light technology, it is difficult to identify and locate arbitrary needle insertion points. Based on the high stability and high accuracy requirements of surgical navigation, this paper proposed a novel method, a muti-modal 3D small object medical marker detection method, which identifies the center of a small single ring as the needle insertion point. Moreover, this novel method leverages Fourier transform enhancement technology to augment the dataset, enrich image details, and enhance the network's capability. The method extracts the Region of Interest (ROI) of the feature image from both enhanced and original images, followed by generating a mask map. Subsequently, the point cloud of the ROI from the depth map is obtained through the registration of ROI point cloud contour fitting. In addition, this method employs Tukey loss for optimal precision. The experimental results show this novel method proposed in this paper not only achieves high-precision and high-stability positioning, but also enables the positioning of any needle insertion point.
Abstract (translated)
导航定位胸腹部穿刺手术中的针头入口点是在患者身体表面的定位。传统的反射球导航方法很难在柔软、不规则、平滑的胸腹部上定位针头入口点。由于使用结构光技术来观察人体表面的结构化光点缺乏明确特征点，因此很难识别和定位任意针头插入点。根据高精度和高准确度手术导航的要求，本文提出了一个新方法，一种多模态3D小物体医学标记检测方法，将小单环的圆心确定为针头插入点。此外，这种新方法利用傅里叶变换增强技术来丰富数据集，增加图像细节，并增强网络的功能。该方法从增强和原始图像中提取目标区域，然后生成掩膜图。接下来，通过目标点云轮廓拟合来获得ROI点云。此外，该方法采用Tukey损失来实现最佳精度。实验结果表明，本文提出的新方法不仅实现了高精度和高稳定性的定位，而且还能够定位任何针头插入点。
URL
https://arxiv.org/abs/2404.08990
