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| Registration for Multi-Modal and Multi-Phase Images of Proximal Femur Based on Voxel Mutual Information |
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1 Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
2 Institute of Orthopedics in PLA General Hospital, Beijing 100853, China |
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Abstract Image analysis is a common method for evaluation of proximal femur osteoporosis and femoral head necrosis. This method evaluates patient’s condition based on images of proximal femur with different modes and phases. However, because the images are generated in different systems and the positions of the patient relative to systems are different, the positions of anatomical points in different images are not one-to-one consistent. We need to align points of images with different modes and phases before we can research on interesting area. To solve the problem, we proposed a solution to get spatial rigid transformation through image pre-processing, voxels segmentation of femur based on dualthreshold combined with Bayes decision rule, and femurs registration based on normalized mutual information. The error of CT-MR registration and CT-CT registration were below 4 mm and 2 mm respectively. Using the matrix transfer relationship, rigid transformation between any two images based on multiphase CT-CT registration matrix was obtained. On this basis, image fusion of any two images, point-to-point analysis and quantitative evaluation of osseous and blood supply condition were processed. The interesting area in images with different modes and phases through the solution was compared.
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