3D Intra-articular Dense Reconstruction from Arthroscopic Images
- Publisher:
- IEEE
- Publication Type:
- Conference Proceeding
- Citation:
- 2023 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2023, 00, pp. 1-7
- Issue Date:
- 2023-12-22
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| 3D_Intra-articular_Dense_Reconstruction_from_Arthroscopic_Images.pdf | Accepted version | 3.24 MB |
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Arthroscopy is an important clinical technique for knee joint damage treatment where a small fibre optic camera is manipulated in a narrow space to provide a live 2D view of the inner joint The small field of view from the surgical scope makes the 3D guidance for instruments manipulation very difficult Therefore a 3D reconstruction of the articular surface becomes very helpful This paper provides a framework that recovers joint inner dense surface for arthroscopy using only a sequence of intra articular images A self supervised convolutional neural network is trained pre operatively to predict dense depth maps from the intra articular images The depth maps and images are fused together and a local to global SLAM pipeline is proposed for tissue surface reconstruction Compared with existing works on 3D reconstruction using arthroscopic images the proposed framework does not require additional sensors Ex vivo experiments are conducted and the result demonstrates reconstruction ability as well as the potential clinical value of this framework
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