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Automatic Prospective Registration of High-Resolution Trabecular Bone Images of the Tibia

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Abstract

Magnetic Resonance Imaging (MRI) longitudinal studies conducted to assess changes in tibia bone quality impose strict requirements on the reproducibility of the prescribed region acquired. Registration, the process of aligning two images, is commonly performed on the images after acquisition. However, techniques to improve image registration precision by adjusting scanning parameters prospectively, prior to image acquisition, would be preferred. We have adapted an automatic prospective mutual information based registration algorithm to a MRI longitudinal study of trabecular bone of the tibia and compared it to a post-scan manual registration. Qualitatively, image alignment due to the prospective registration is shown in 2D subtraction images and 3D surface renderings. Quantitatively, the registration performance is demonstrated by calculating the sum of the squares of the subtraction images. Results show that the sum of the squares is lower for the follow up images with prospective registration by an average of 19.37% ± 0.07 compared to follow up images with post-scan manual registration. Our study found no significant difference between the trabecular bone structure parameters calculated from the post-scan manual registration and the prospective registration images (p > 0.05). All coefficient of variation values for all trabecular bone structure parameters were within a 2–4.5% range which are within values previously reported in the literature. Results suggest that this algorithm is robust enough to be used in different musculoskeletal imaging applications including the hip as well as the tibia.

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Acknowledgments

This work is funded by NIH grant award program number ROI-AR49701. The authors thank David Newitt and Ben Hyun for their insight on trabecular bone analysis.

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Authors and Affiliations

  1. Department of Radiology, University of California, 1700 4th St., Suite 203, Box 2520, San Francisco, CA, 94107, USA

    Janet Blumenfeld, Julio Carballido-Gamio, Roland Krug & Sharmila Majumdar

  2. UCSF-UCB Joint Graduate Group in Bioengineering, San Francisco, CA, USA

    Janet Blumenfeld

  3. GE Global Research Center, Niskayuna, NY, USA

    Daniel J. Blezek & Ileana Hancu

Authors
  1. Janet Blumenfeld
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  2. Julio Carballido-Gamio
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  3. Roland Krug
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  4. Daniel J. Blezek
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  5. Ileana Hancu
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  6. Sharmila Majumdar
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Correspondence to Janet Blumenfeld.

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Blumenfeld, J., Carballido-Gamio, J., Krug, R. et al. Automatic Prospective Registration of High-Resolution Trabecular Bone Images of the Tibia. Ann Biomed Eng 35, 1924–1931 (2007). https://doi.org/10.1007/s10439-007-9365-z

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  • DOI: https://doi.org/10.1007/s10439-007-9365-z

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