Visual Servoing under Limited Field of View (FOV) for Lumbar Vertebrae Positioning

X-ray machines are vital in medical imaging for viewing internal body structures. However, in lumbar vertebrae surgery, the X-ray machine has to move and position frequently and manually, which risks infection, misalignment, and overexposure to radiation. There’s a need for mobile X-ray machines with autonomous recognition and positioning. Although visual servoing suitable for X-ray positioning naturally, it still experiencing challenges like limited Field-of-View (FOV) and the structural similarity among vertebrae. In this paper, a Bayesian Estimation based approach is developed to improve the detection accuracy in case of vertebrae positions outside the FOV. Furthermore, a visual servoing method is proposed for X-ray positioning, considering their mechanical structure and imaging characteristics. The experiment results indicates that the proposed approach improves lumbar vertebrae detection accuracy significantly. This approach facilitates precise positioning in X-ray imaging and enhances the safety and effectiveness of lumbar vertebrae surgery.

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Publication Details

Published
2025-03-14
DOI
https://doi.org/10.1109/itoec63606.2025.10967573
Primary Topic
Medical Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Visual Servoing under Limited Field of View (FOV) for Lumbar Vertebrae Positioning

Peng Xiao, Bo Song, Le Zou, Xiaofeng Wang et al.
Medical Imaging and Analysis
article

Visual Servoing under Limited Field of View (FOV) for Lumbar Vertebrae Positioning

Peng Xiao, Bo Song, Le Zou, Xiaofeng Wang, Yu Wang, Bin Cai, Zhiyong Sun, Chi Xiong, Lingming Kong
article en

Abstract

X-ray machines are vital in medical imaging for viewing internal body structures. However, in lumbar vertebrae surgery, the X-ray machine has to move and position frequently and manually, which risks infection, misalignment, and overexposure to radiation. There’s a need for mobile X-ray machines with autonomous recognition and positioning. Although visual servoing suitable for X-ray positioning naturally, it still experiencing challenges like limited Field-of-View (FOV) and the structural similarity among vertebrae. In this paper, a Bayesian Estimation based approach is developed to improve the detection accuracy in case of vertebrae positions outside the FOV. Furthermore, a visual servoing method is proposed for X-ray positioning, considering their mechanical structure and imaging characteristics. The experiment results indicates that the proposed approach improves lumbar vertebrae detection accuracy significantly. This approach facilitates precise positioning in X-ray imaging and enhances the safety and effectiveness of lumbar vertebrae surgery.

Chinese Academy of Sciences (CN), Hefei University (CN), Institute of Intelligent Machines (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 92%
Medical Imaging and Analysis
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