Joint surface reconstruction and 4D deformation estimation from sparse data and prior knowledge for marker-less Respiratory motion tracking

被引:4
作者
Berkels, Benjamin [1 ,5 ]
Bauer, Sebastian [2 ,6 ]
Ettl, Svenja [3 ]
Arold, Oliver [3 ]
Hornegger, Joachim [2 ,4 ,7 ]
Rumpf, Martin [1 ]
机构
[1] Univ Bonn, Inst Numer Simulat, D-53115 Bonn, Germany
[2] Univ Erlangen Nurnberg, Dept Comp Sci, Pattern Recognit Lab, D-91058 Erlangen, Germany
[3] Univ Erlangen Nurnberg, Inst Opt Informat & Photon, D-91058 Erlangen, Germany
[4] Erlangen Grad Sch Adv Opt Technol SAOT, D-91058 Erlangen, Germany
[5] Univ S Carolina, Interdisciplinary Math Inst, Columbia, SC 29208 USA
[6] Tech Univ Munich, GSISH, D-80290 Munich, Germany
[7] Univ Erlangen Nurnberg, Erlangen Grad Sch Adv Opt Technol SAOT, D-91058 Erlangen, Germany
关键词
radiation therapy; respiratory motion; motion modeling; surface registration; nonrigid registration; inverse-consistent registration; range imaging; TUMOR TRACKING; QUALITY-ASSURANCE; IMAGING-SYSTEM; RADIOTHERAPY; ACCURACY; CAMERA; MODEL;
D O I
10.1118/1.4816675
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: The intraprocedural tracking of respiratory motion has the potential to substantially improve image-guided diagnosis and interventions. The authors have developed a sparse-to-dense registration approach that is capable of recovering the patient's external 3D body surface and estimating a 4D (3D + time) surface motion field from sparse sampling data and patient-specific prior shape knowledge. Methods: The system utilizes an emerging marker-less and laser-based active triangulation (AT) sensor that delivers sparse but highly accurate 3D measurements in real-time. These sparse position measurements are registered with a dense reference surface extracted from planning data. Thereby a dense displacement field is recovered, which describes the spatio-temporal 4D deformation of the complete patient body surface, depending on the type and state of respiration. It yields both a reconstruction of the instantaneous patient shape and a high-dimensional respiratory surrogate for respiratory motion tracking. The method is validated on a 4D CT respiration phantom and evaluated on both real data from an AT prototype and synthetic data sampled from dense surface scans acquired with a structured-light scanner. Results: In the experiments, the authors estimated surface motion fields with the proposed algorithm on 256 datasets from 16 subjects and in different respiration states, achieving a mean surface reconstruction accuracy of +/- 0.23 mm with respect to ground truth data-down from a mean initial surface mismatch of 5.66 mm. The 95th percentile of the local residual mesh-to-mesh distance after registration did not exceed 1.17 mm for any subject. On average, the total runtime of our proof of concept CPU implementation is 2.3 s per frame, outperforming related work substantially. Conclusions: In external beam radiation therapy, the approach holds potential for patient monitoring during treatment using the reconstructed surface, and for motion-compensated dose delivery using the estimated 4D surface motion field in combination with external-internal correlation models. (C) 2013 American Association of Physicists in Medicine.
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页数:10
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