1. Spatiotemporal motion estimation for respiratory-correlated imaging of the lungs
- Author
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Jef Vandemeulebroucke, Simon Rit, Jan Kybic, Patrick Clarysse, David Sarrut, Calvat, Pascal, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'InfoRmatique en Image et Systèmes d'information ( LIRIS ), Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ) -Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Center for Machine Perception, Czech Technical University in Prague ( CTU ), 4 - Imagerie Tomographique et Radiothérapie, Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), CCIN2P3, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Imagerie Tomographique et Radiothérapie, Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Czech Technical University in Prague (CTU), and Electronics and Informatics
- Subjects
Time Factors ,respiratory motion ,MESH : Movement ,MESH : Four-Dimensional Computed Tomography ,Movement ,MESH : Lung ,Diaphragm ,Physics::Medical Physics ,MESH: Movement ,MESH : Models, Biological ,Thoracic Radiotherapy ,Models, Biological ,MESH : Artifacts ,4D Ct ,Deformable Registration ,Image Processing, Computer-Assisted ,Organ Motion ,MESH: Lung ,[ SDV.IB ] Life Sciences [q-bio]/Bioengineering ,Four-Dimensional Computed Tomography ,4-Dimensional Computed-Tomography ,Lung ,Ct ,Deformations ,MESH: Respiration ,[SDV.IB] Life Sciences [q-bio]/Bioengineering ,MESH: Four-Dimensional Computed Tomography ,Respiration ,MESH: Time Factors ,MESH: Models, Biological ,MESH: Image Processing, Computer-Assisted ,MESH : Respiration ,Mr-Images ,MESH: Artifacts ,MESH: Diaphragm ,Nonrigid Registration ,[SDV.IB]Life Sciences [q-bio]/Bioengineering ,Reconstruction ,MESH : Diaphragm ,Artifacts ,MESH : Image Processing, Computer-Assisted ,Model ,MESH : Time Factors - Abstract
International audience; PURPOSE: Four-dimensional computed tomography (4D CT) can provide patient-specific motion information for radiotherapy planning and delivery. Motion estimation in 4D CT is challenging due to the reduced image quality and the presence of artifacts. We aim to improve the robustness of deformable registration applied to respiratory-correlated imaging of the lungs, by using a global problem formulation and pursuing a restrictive parametrization for the spatiotemporal deformation model. METHODS: A spatial transformation based on free-form deformations was extended to the temporal domain, by explicitly modeling the trajectory using a cyclic temporal model based on B-splines. A global registration criterion allowed to consider the entire image sequence simultaneously and enforce the temporal coherence of the deformation throughout the respiratory cycle. To ensure a parametrization capable of capturing the dynamics of respiratory motion, a prestudy was performed on the temporal dimension separately. The temporal parameters were tuned by fitting them to diaphragm motion data acquired for a large patient group. Suitable properties were retained and applied to spatiotemporal registration of 4D CT data. Registration results were validated using large sets of landmarks and compared to consecutive spatial registrations. To illustrate the benefit of the spatiotemporal approach, we also assessed the performance in the presence of motion-induced artifacts. RESULTS: Cubic B-splines gave better or similar fitting results as lower orders and were selected because of their inherently stronger regularization. The fitting and registration errors increased gradually with the temporal control point spacing, representing a trade-off between achievable accuracy and sensitivity to noise and artifacts. A piecewise smooth trajectory model, allowing for a discontinuous change of speed at end-inhale, was found most suitable to account for the sudden changes of motion at this breathing phase. The spatiotemporal modeling allowed a reduction of the number of parameters of 45%, while maintaining registration accuracy within 0.1 mm. The approach reduced the sensitivity to artifacts. CONCLUSIONS: Spatiotemporal registration can provide accurate motion estimation for 4D CT and improves the robustness to artifacts.
- Published
- 2011