2020
DOI: 10.1088/1361-6560/ab501d
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Abstract: Image-guided radiation therapy (IGRT) allows radiation dose deposition with a high degree of geometric accuracy. Previous studies have demonstrated that such therapies may benefit from the employment of deformable image registration (DIR) algorithms, which allow both the automatic tracking of anatomical changes and accumulation of the delivered radiation dose over time. In order to ensure patient care and safety, however, the estimated deformations must be subjected to stringent quality assurance (QA) measures… Show more

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Cited by 11 publications
(22 citation statements)
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References 49 publications
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“…While there are many registration algorithms available in the literature, very few fulfil these requirements, and even fewer have been validated for clinical use. For this work, we selected EVolution based on its demonstrated accurate performance for MR-to-MR contour propagation [18] , [20] . The results obtained in the current study are in good correspondence with previous reports, since EVolution delivered overall clinically usable propagated contours.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…While there are many registration algorithms available in the literature, very few fulfil these requirements, and even fewer have been validated for clinical use. For this work, we selected EVolution based on its demonstrated accurate performance for MR-to-MR contour propagation [18] , [20] . The results obtained in the current study are in good correspondence with previous reports, since EVolution delivered overall clinically usable propagated contours.…”
Section: Discussionmentioning
confidence: 99%
“…The algorithm optimizes the local alignment between similar contrast patterns within the registered images, making it suitable for both mono- and multi-modal image registration. The algorithm was primarily chosen due to its previously demonstrated clinically-acceptable accuracy for contour propagation [18] , [20] . Moreover, the method is highly parallelizable, facilitating a fast convergence of < 2 sec for mono-modal MRI registration (256 × 256 × 128 image size) using the Compute Unified Device Architecture (CUDA) and when performed on a NVidia TITAN V graphics processing unit.…”
Section: Methodsmentioning
confidence: 99%
“…Concerning abdominal organs, it must be underlined that deformations are non-rigid and thus extension of our framework to non-rigid registration would be required. For instance, recent works conducted in the abdomen used biomechanical criteria to assess image registration accuracy (Zachiu et al 2018) (Zachiu et al 2020). Such approaches involve the estimation of mechanical stress, which would occur within the observed tissues.…”
Section: Discussionmentioning
confidence: 99%
“…Recent studies have investigated the potential of radiomics for precision RT [19] , [83] , [84] , [85] . Of note, for high quality usage of functional and anatomic imaging data, dedicated robust strategies for image registration [86] , [87] , [88] , [89] and data analysis [90] are needed. Only then, reliable new segmentation algorithms [91] , [92] and prediction models can be trained [16] , [93] .…”
Section: Image Data Processing Analysis and Radiomicsmentioning
confidence: 99%