2010
DOI: 10.1120/jacmp.v11i3.3175
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Assessment of a commercially available automatic deformable registration system

Abstract: In recent years, a number of approaches have been applied to the problem of deformable registration validation. However, the challenge of assessing a commercial deformable registration system – in particular, an automatic registration system in which the deformable transformation is not readily accessible – has not been addressed. Using a collection of novel and established methods, we have developed a comprehensive, four‐component protocol for the validation of automatic deformable image registration systems … Show more

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Cited by 25 publications
(15 citation statements)
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References 49 publications
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“…A potential solution to extend the coverage would be to use the HNS coil and then apply a robust, non-rigid body registration algorithm capable of local deformations [19], and this is the subject of ongoing work. However, in future, it is expected that vendors will bring to market more dedicated RF coils that will allow the acquisition of treatment position images across a number of sites.…”
Section: Discussionmentioning
confidence: 99%
“…A potential solution to extend the coverage would be to use the HNS coil and then apply a robust, non-rigid body registration algorithm capable of local deformations [19], and this is the subject of ongoing work. However, in future, it is expected that vendors will bring to market more dedicated RF coils that will allow the acquisition of treatment position images across a number of sites.…”
Section: Discussionmentioning
confidence: 99%
“…Kirby et al 24 found that a higher value of the smoothness parameter improved the overall spatial accuracy, but this came with a diminishing ability to transfer contours. Fallone et al 26 found that commercial systems are more apt to account for global deformations than local variations.…”
Section: B Dir Validation In the Literaturementioning
confidence: 99%
“…Large differences in accuracy between algorithms were found, also depending on the image region. [24][25][26][27][28][29][30] Two important techniques for evaluating the spatial accuracy of DIR involve landmark tracking 28,29,31 and contour or structure comparison. 20,21,32 Structure correspondence is quantified with metrics such as average surface distance error (SDE), Hausdorff distance (HD), and Dice similarity coefficient (DSC).…”
Section: Introductionmentioning
confidence: 99%
“…A crucial issue is the preservation of topology in the computation of the deformation field, to maintain neighborhood relationships and integrity of anatomical structures (19). Assessing the clinical validity of DIR is a complex task (19,20) and appropriate validation study at each anatomical site are needed (3). Comparative studies have been performed, relying on either deformable phantoms or common datasets with verification landmarks or structures segmented by experts (10)(11)(12)(13).…”
Section: Technology In Cancer Research and Treatment Volume 12 Numbermentioning
confidence: 99%