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Optimal setting of image bounding box can improve registration accuracy of diffusion tensor tractography

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

When we register diffusion tensor tractography (DTT) to anatomical images such as fast imaging employing steady-state acquisition (FIESTA), we register the B0 image to FIESTA. Precise registration of the DTT B0 image to FIESTA is possible with non-rigid registration compared to rigid registration, although the non-rigid methods lack convenience. We report the effect of image data bounding box settings on registration accuracy using a normalized mutual information (NMI) method

Methods

MRI scans of 10 patients were used in this study. Registration was performed without modification of the bounding box in the control group, and the results were compared with groups re-registered using multiple bounding boxes limited to the region of interest (ROI). The distance of misalignment after registration at 3 anatomical characteristic points that are common to both FIESTA and B0 images was used as an index of accuracy.

Results

Mean (\(\pm \)SD) misalignment at the 3 anatomical points decreased significantly from \(5.99\pm 1.58\) to \(2.21\pm 1.24\) mm, \(p<0.0001\)), \(4.36\pm 1.58\) to \(1.48\pm 0.58\) mm, (\(p<0.0001)\), and \(5.21\pm 1.76\) to \(1.20\pm 0.74\) mm, (\(p<0.0001)\), each showing improvement compared to the control group

Conclusion

Narrowing the image data bounding box to the ROI improves the accuracy of registering B0 images to FIESTA by NMI method. With our proposed methodology, accuracy can be improved in extremely easy steps, and this methodology may prove useful for DTT registration to anatomical image

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Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Department of Neurosurgery, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan

    Masanori Yoshino, Taichi Kin, Daichi Nakagawa, Hirofumi Nakatomi & Nobuhito Saito

  2. Department of Clinical Information Engineering, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan

    Toki Saito & Hiroshi Oyama

  3. Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan

    Akira Kunimatsu

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  1. Masanori Yoshino
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  2. Taichi Kin
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Correspondence to Masanori Yoshino.

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Yoshino, M., Kin, T., Saito, T. et al. Optimal setting of image bounding box can improve registration accuracy of diffusion tensor tractography. Int J CARS 9, 333–339 (2014). https://doi.org/10.1007/s11548-013-0934-3

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  • DOI: https://doi.org/10.1007/s11548-013-0934-3

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