OBJECTIVE: This work evaluates current 3-D image registration tools on clinically acquired abdominal computed tomography (CT) scans. METHODS: Thirteen abdominal organs were manually labeled on a set of 100 CT images, and the 100 labeled images (i.e., atlases) were pairwise registered based on intensity information with six registration tools (FSL, ANTS-CC, ANTS-QUICK-MI, IRTK, NIFTYREG, and DEEDS). The Dice similarity coefficient (DSC), mean surface distance, and Hausdorff distance were calculated on the registered organs individually. Permutation tests and indifference-zone ranking were performed to examine the statistical and practical significance, respectively. RESULTS: The results suggest that DEEDS yielded the best registration performance. However, due to the overall low DSC values, and substantial portion of low-performing outliers, great care must be taken when image registration is used for local interpretation of abdominal CT. CONCLUSION: There is substantial room for improvement in image registration for abdominal CT. SIGNIFICANCE: All data and source code are available so that innovations in registration can be directly compared with the current generation of tools without excessive duplication of effort.
OBJECTIVE: This work evaluates current 3-D image registration tools on clinically acquired abdominal computed tomography (CT) scans. METHODS: Thirteen abdominal organs were manually labeled on a set of 100 CT images, and the 100 labeled images (i.e., atlases) were pairwise registered based on intensity information with six registration tools (FSL, ANTS-CC, ANTS-QUICK-MI, IRTK, NIFTYREG, and DEEDS). The Dice similarity coefficient (DSC), mean surface distance, and Hausdorff distance were calculated on the registered organs individually. Permutation tests and indifference-zone ranking were performed to examine the statistical and practical significance, respectively. RESULTS: The results suggest that DEEDS yielded the best registration performance. However, due to the overall low DSC values, and substantial portion of low-performing outliers, great care must be taken when image registration is used for local interpretation of abdominal CT. CONCLUSION: There is substantial room for improvement in image registration for abdominal CT. SIGNIFICANCE: All data and source code are available so that innovations in registration can be directly compared with the current generation of tools without excessive duplication of effort.
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