Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT.

Xu Z, Lee CP, Heinrich MP, Modat M, Rueckert D, Ourselin S, Abramson RG, Landman BA
IEEE Trans Biomed Eng. 2016 63 (8): 1563-72

PMID: 27254856 · PMCID: PMC4972188 · DOI:10.1109/TBME.2016.2574816

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.

MeSH Terms (6)

Abdomen Algorithms Humans Image Processing, Computer-Assisted Radiography, Abdominal Tomography, X-Ray Computed

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