Literature DB >> 23959670

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

Masanori Yoshino1, Taichi Kin, Toki Saito, Daichi Nakagawa, Hirofumi Nakatomi, Akira Kunimatsu, Hiroshi Oyama, Nobuhito Saito.   

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 ([Formula: see text]SD) misalignment at the 3 anatomical points decreased significantly from [Formula: see text] to [Formula: see text] mm, [Formula: see text]), [Formula: see text] to [Formula: see text] mm, ([Formula: see text], and [Formula: see text] to [Formula: see text] mm, ([Formula: see text], 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.

Entities:  

Year:  2013        PMID: 23959670     DOI: 10.1007/s11548-013-0934-3

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


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Journal:  Int J Comput Assist Radiol Surg       Date:  2014-11-20       Impact factor: 2.924

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