Registration of 2D to 3D joint images using phase-based mutual information

Rupin Dalvi; Rafeef Abugharbieh; Mark Pickering; Jennie Scarvell; Paul Smith

doi:10.1117/12.709118

3 March 2007 Registration of 2D to 3D joint images using phase-based mutual information

Rupin Dalvi, Rafeef Abugharbieh, Mark Pickering, Jennie Scarvell, Paul Smith

Proceedings Volume 6512, Medical Imaging 2007: Image Processing; 651209 (2007) https://doi.org/10.1117/12.709118
Event: Medical Imaging, 2007, San Diego, CA, United States

Abstract

Registration of two dimensional to three dimensional orthopaedic medical image data has important applications particularly in the area of image guided surgery and sports medicine. Fluoroscopy to computer tomography (CT) registration is an important case, wherein digitally reconstructed radiographs derived from the CT data are registered to the fluoroscopy data. Traditional registration metrics such as intensity-based mutual information (MI) typically work well but often suffer from gross misregistration errors when the image to be registered contains a partial view of the anatomy visible in the target image. Phase-based MI provides a robust alternative similarity measure which, in addition to possessing the general robustness and noise immunity that MI provides, also employs local phase information in the registration process which makes it less susceptible to the aforementioned errors. In this paper, we propose using the complex wavelet transform for computing image phase information and incorporating that into a phase-based MI measure for image registration. Tests on a CT volume and 6 fluoroscopy images of the knee are presented. The femur and the tibia in the CT volume were individually registered to the fluoroscopy images using intensity-based MI, gradient-based MI and phase-based MI. Errors in the coordinates of fiducials present in the bone structures were used to assess the accuracy of the different registration schemes. Quantitative results demonstrate that the performance of intensity-based MI was the worst. Gradient-based MI performed slightly better, while phase-based MI results were the best consistently producing the lowest errors.

Citation Download Citation

Rupin Dalvi, Rafeef Abugharbieh, Mark Pickering, Jennie Scarvell, and Paul Smith "Registration of 2D to 3D joint images using phase-based mutual information", Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651209 (3 March 2007); https://doi.org/10.1117/12.709118

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