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Objective assessment of deformable image registration in radiotherapy: A multi‐institution study
Author(s) -
Kashani Rojano,
Hub Martina,
Balter James M.,
Kessler Marc L.,
Dong Lei,
Zhang Lifei,
Xing Lei,
Xie Yaoqin,
Hawkes David,
Schnabel Julia A.,
McClelland Jamie,
Joshi Sarang,
Chen Quan,
Lu Weiguo
Publication year - 2008
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3013563
Subject(s) - imaging phantom , image registration , classification of discontinuities , computer science , artificial intelligence , contrast (vision) , computer vision , ground truth , discontinuity (linguistics) , medical imaging , image (mathematics) , mathematics , nuclear medicine , medicine , mathematical analysis
The looming potential of deformable alignment tools to play an integral role in adaptive radiotherapy suggests a need for objective assessment of these complex algorithms. Previous studies in this area are based on the ability of alignment to reproduce analytically generated deformations applied to sample image data, or use of contours or bifurcations as ground truth for evaluation of alignment accuracy. In this study, a deformable phantom was embedded with 48 small plastic markers, placed in regions varying from high contrast to roughly uniform regional intensity, and small to large regional discontinuities in movement. CT volumes of this phantom were acquired at different deformation states. After manual localization of marker coordinates, images were edited to remove the markers. The resulting image volumes were sent to five collaborating institutions, each of which has developed previously published deformable alignment tools routinely in use. Alignments were done, and applied to the list of reference coordinates at the inhale state. The transformed coordinates were compared to the actual marker locations at exhale. A total of eight alignment techniques were tested from the six institutions. All algorithms performed generally well, as compared to previous publications. Average errors in predicted location ranged from 1.5 to 3.9 mm , depending on technique. No algorithm was uniformly accurate across all regions of the phantom, with maximum errors ranging from 5.1 to 15.4 mm . Larger errors were seen in regions near significant shape changes, as well as areas with uniform contrast but large local motion discontinuity. Although reasonable accuracy was achieved overall, the variation of error in different regions suggests caution in globally accepting the results from deformable alignment.