Publication | Open Access
Review and recommendations on deformable image registration uncertainties for radiotherapy applications
63
Citations
186
References
2023
Year
EngineeringRadiotherapy ApplicationsDiagnosisSurgeryDir AlgorithmsImage AnalysisImage RegistrationRadiation Therapy PlanningComputational GeometryRadiation OncologyNuclear MedicineRadiologyAdaptive RadiotherapyGeometric ModelingMedical ImagingDeformable Image RegistrationImage GuidanceMedical Image ComputingBiomedical ImagingDir UncertaintiesMedicineMedical Image Analysis
Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.
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