ERegPose: An explicit regression based 6D pose estimation for snake-like wrist-type surgical instruments

IF 2.3 3区医学 Q2 SURGERY

International Journal of Medical Robotics and Computer Assisted Surgery Pub Date : 2024-05-24 DOI:10.1002/rcs.2640

Jinhua Li, Zhengyang Ma, Xinan Sun, He Su

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引用次数: 0

Abstract

Background

Accurately estimating the 6D pose of snake-like wrist-type surgical instruments is challenging due to their complex kinematics and flexible design.

Methods

We propose ERegPose, a comprehensive strategy for precise 6D pose estimation. The strategy consists of two components: ERegPoseNet, an original deep neural network model designed for explicit regression of the instrument's 6D pose, and an annotated in-house dataset of simulated surgical operations. To capture rotational features, we employ an Single Shot multibox Detector (SSD)-like detector to generate bounding boxes of the instrument tip.

Results

ERegPoseNet achieves an error of 1.056 mm in 3D translation, 0.073 rad in 3D rotation, and an average distance (ADD) metric of 3.974 mm, indicating an overall spatial transformation error. The necessity of the SSD-like detector and L1 loss is validated through experiments.

Conclusions

ERegPose outperforms existing approaches, providing accurate 6D pose estimation for snake-like wrist-type surgical instruments. Its practical applications in various surgical tasks hold great promise.

查看原文本刊更多论文

ERegPose：基于显式回归的蛇形腕式手术器械 6D 姿势估计。

背景：由于蛇形腕式手术器械运动学复杂，设计灵活，因此准确估计其 6D 姿态具有挑战性：我们提出了ERegPose--一种用于精确估计6D姿态的综合策略。该策略由两部分组成：ERegPoseNet是一个原创的深度神经网络模型，旨在对器械的6D姿态进行显式回归；ERegPoseNet还包括一个带有注释的模拟手术操作内部数据集。为了捕捉旋转特征，我们采用了类似于单射多框检测器（SSD）的检测器来生成器械尖端的边界框：结果：ERegPoseNet 的三维平移误差为 1.056 毫米，三维旋转误差为 0.073 拉德，平均距离 (ADD) 指标为 3.974 毫米，表明存在整体空间转换误差。通过实验验证了类 SSD 检测器和 L1 损失的必要性：ERegPose优于现有方法，可为蛇形腕式手术器械提供精确的6D姿态估计。它在各种手术任务中的实际应用前景广阔。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Medical Robotics and Computer Assisted Surgery 医学-外科

CiteScore

4.50

自引率

12.00%

发文量

131

审稿时长

6-12 weeks

期刊介绍： The International Journal of Medical Robotics and Computer Assisted Surgery provides a cross-disciplinary platform for presenting the latest developments in robotics and computer assisted technologies for medical applications. The journal publishes cutting-edge papers and expert reviews, complemented by commentaries, correspondence and conference highlights that stimulate discussion and exchange of ideas. Areas of interest include robotic surgery aids and systems, operative planning tools, medical imaging and visualisation, simulation and navigation, virtual reality, intuitive command and control systems, haptics and sensor technologies. In addition to research and surgical planning studies, the journal welcomes papers detailing clinical trials and applications of computer-assisted workflows and robotic systems in neurosurgery, urology, paediatric, orthopaedic, craniofacial, cardiovascular, thoraco-abdominal, musculoskeletal and visceral surgery. Articles providing critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies, commenting on ease of use, or addressing surgical education and training issues are also encouraged. The journal aims to foster a community that encompasses medical practitioners, researchers, and engineers and computer scientists developing robotic systems and computational tools in academic and commercial environments, with the intention of promoting and developing these exciting areas of medical technology.