A system for the registration of arthroscopic images to magnetic resonance images of the knee: for improved virtual knee arthroscopy

Chengliang Hu; Giancarlo Amati; Nicola Gullick; Stephen Oakley; Vassilios Hurmusiadis; Tobias Schaeffter; Graeme Penney; Kawal Rhode

doi:10.1117/12.813775

13 March 2009 A system for the registration of arthroscopic images to magnetic resonance images of the knee: for improved virtual knee arthroscopy

Chengliang Hu, Giancarlo Amati, Nicola Gullick, Stephen Oakley, Vassilios Hurmusiadis, Tobias Schaeffter, Graeme Penney, Kawal Rhode

Author Affiliations +

Proceedings Volume 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling; 726119 (2009) https://doi.org/10.1117/12.813775
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Knee arthroscopy is a minimally invasive procedure that is routinely carried out for the diagnosis and treatment of pathologies of the knee joint. A high level of expertise is required to carry out this procedure and therefore the clinical training is extensive. There are several reasons for this that include the small field of view seen by the arthroscope and the high degree of distortion in the video images. Several virtual arthroscopy simulators have been proposed to augment the learning process. One of the limitations of these simulators is the generic models that are used. We propose to develop a new virtual arthroscopy simulator that will allow the use of pathology-specific models with an increased level of photo-realism. In order to generate these models we propose to use registered magnetic resonance images (MRI) and arthroscopic video images collected from patients with a variety of knee pathologies. We present a method to perform this registration based on the use of a combined X-ray and MR imaging system (XMR). In order to validate our technique we carried out MR imaging and arthroscopy of a custom-made acrylic phantom in the XMR environment. The registration between the two modalities was computed using a combination of XMR and camera calibration, and optical tracking. Both two-dimensional (2D) and three-dimensional (3D) registration errors were computed and shown to be approximately 0.8 and 3 mm, respectively. Further to this, we qualitatively tested our approach using a more realistic plastic knee model that is used for the arthroscopy training.

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Chengliang Hu, Giancarlo Amati, Nicola Gullick, Stephen Oakley, Vassilios Hurmusiadis, Tobias Schaeffter, Graeme Penney, and Kawal Rhode "A system for the registration of arthroscopic images to magnetic resonance images of the knee: for improved virtual knee arthroscopy", Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 726119 (13 March 2009); https://doi.org/10.1117/12.813775

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