<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xu, Zhoubing</style></author><author><style face="normal" font="default" size="100%">Lee, Christopher P</style></author><author><style face="normal" font="default" size="100%">Heinrich, Mattias P.</style></author><author><style face="normal" font="default" size="100%">Modat, Marc</style></author><author><style face="normal" font="default" size="100%">Rueckert, Daniel</style></author><author><style face="normal" font="default" size="100%">Ourselin, Sebastien</style></author><author><style face="normal" font="default" size="100%">Abramson, Richard G</style></author><author><style face="normal" font="default" size="100%">Landman, Bennett A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT.</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE transactions on bio-medical engineering</style></secondary-title><alt-title><style face="normal" font="default" size="100%">IEEE Trans Biomed Eng</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Aug</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">63</style></volume><pages><style face="normal" font="default" size="100%">1563-72</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/27254856?dopt=Abstract</style></custom1></record></records></xml>