23 February 2010 Multi-slice to volume registration of ultrasound data to a statistical atlas of human pelvis
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Abstract
Identifying the proper orientation of the pelvis is a critical step in accurate placement of the femur prosthesis in the acetabulum in Total Hip Replacement (THR) surgeries. The general approach to localize the orientation of the pelvis coordinate system is to use X-ray fluoroscopy to guide the procedure. An alternative can be employing intra-operative ultrasound (US) imaging with pre-operative CT scan or fluoroscopy imaging. In this paper, we propose to replace the need of pre-operative imaging by using a statistical shape model of the pelvis, constructed from several CT images. We then propose an automatic deformable intensity-based registration of the anatomical atlas to a sparse set of 2D ultrasound images of the pelvis in order to localize its anatomical coordinate system. In this registration technique, we first extract a set of 2D slices from a single instance of the pelvic atlas. Each individual 2D slice is generated based on the location of a corresponding 2D ultrasound image. Next, we create simulated ultrasound images out of the 2D atlas slices and calculate a similarity metric between the simulated images and the actual ultrasound images. The similarity metric guides an optimizer to generate an instance of the atlas that best matches the ultrasound data. We demonstrated the feasibility of our proposed approach on two male human cadaver data. The registration was able to localize a patient-specific pelvic coordinate system with origin translation error of 2 mm and 3.45 mm, and average axes rotation error of 3.5 degrees and 3.9 degrees for the two cadavers, respectively.
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Sahar Ghanavati, Sahar Ghanavati, Parvin Mousavi, Parvin Mousavi, Gabor Fichtinger, Gabor Fichtinger, Pezhman Foroughi, Pezhman Foroughi, Purang Abolmaesumi, Purang Abolmaesumi, } "Multi-slice to volume registration of ultrasound data to a statistical atlas of human pelvis", Proc. SPIE 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, 76250O (23 February 2010); doi: 10.1117/12.844080; https://doi.org/10.1117/12.844080
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