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Soft-tissue sound-speed-aware ultrasound-CT registration method for computer-assisted orthopedic surgery

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Abstract

Ultrasound (US) has been introduced to computer-assisted orthopedic surgery for bone registration owing to its advantages of nonionizing radiation, low cost, and noninvasiveness. However, the registration accuracy is limited by US image distortion caused by variations in the acoustic properties of soft tissues. This paper proposes a soft-tissue sound-speed-aware registration method to overcome the above challenge. First, the feature enhancement strategy of multi-channel overlay is proposed for U2-net to improve bone segmentation performance. Secondly, the sound speed of soft tissue is estimated by simulating the bone surface distance map for the update of US-derived points. Finally, an iterative registration strategy is adopted to optimize the registration result. A phantom experiment was conducted using different registration methods for the femur and tibia/fibula. The fiducial registration error (femur, 0.98 ± 0.08 mm (mean ± SD); tibia/fibula, 1.29 ± 0.19 mm) and the target registration error (less than 2.11 mm) showed the high accuracy of the proposed method. The experimental results suggest that the proposed method can be integrated into navigation systems that provide surgeons with accurate 3D navigation information.

Graphical abstract

First, multi-channel input data including the original image, phase symmetric image, and depth weighted map are fused for U2-net model training in the automatic bone segmentation of US images. When US-derived points are obtained, the sound speed of soft tissue is estimated by simulating the bone surface distance map for the update of the locations of US-derived points. An iterative registration strategy based on the cost function of corresponding point distances is adopted to optimize the registration result. Finally, a gold-standard transformation based on artificial fiducials is constructed for method evaluation.

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Funding

This work was partly supported by the by Tian** Science and Technology Planning Project under Grant 20201193.

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Authors and Affiliations

  1. Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tian** University, Tian**, 300354, China

    Chuanba Liu, Wenshuo Wang, Tao Sun & Yimin Song

  2. International Institute for Innovative Design and Intelligent Manufacturing of Tian** University in Zhejiang, Shaoxing, China

    Chuanba Liu

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Chuanba Liu, and Tao Sun contributed equally to research design, analysis of data, and drafting of the manuscript. Yimin Song contributed equally to critical revisions of the manuscript as well as approval of the final submission. All authors have read and approved the final submitted manuscript.

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Correspondence to Tao Sun.

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This article used anonymous data from an existing collection of CT scans and does not contain any studies with human participants performed by any of the authors. Informed consent for this type of study is not required.

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Liu, C., Wang, W., Sun, T. et al. Soft-tissue sound-speed-aware ultrasound-CT registration method for computer-assisted orthopedic surgery. Med Biol Eng Comput (2024). https://doi.org/10.1007/s11517-024-03123-x

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