Compensation of Some Time Dependent Deformations in Tomography

Desbat, Laurent; Roux, Sébastiên; Grangeat, Pierre

doi:10.1109/tmi.2006.889743

Cited by 46 publications

(38 citation statements)

References 17 publications

(31 reference statements)

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“…In particular, if the patient motion is globally rigid, this amounts to using virtual source and detector positions and applying the reconstruction algorithm as in the static case [11], [12], [13] or to deform data prior to reconstruction [14], [15]. These approaches can be generalized to deformations transforming the set of acquisition lines of each cone beam projection into other sets of concurent lines [9], [10], [16]. Thus, analytic approaches essentially allow for the compensation of deformations in subclasses of those presented in section I-B.…”

Section: Dynamic Reconstruction Approachesmentioning

confidence: 99%

“…We recall briefly in this section a class of 3D deformations which can be analytically compensated in 3D Cone Beam reconstruction, see [23] and [16], [10] for 2D fan-beam dynamic tomography. In order to stay in the framework of 3D CB reconstruction, we consider the deformations Γ t which transform the set of convergent acquisition lines at time t into an other set of convergent lines at the reference time, i.e.…”

Section: Analytic Dynamic Reconstructionmentioning

confidence: 99%

See 1 more Smart Citation

Algebraic and analytic reconstruction methods for dynamic tomography

Desbat

Rit

Clackdoyle³

et al. 2007

2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Section: Dynamic Reconstruction Approachesmentioning

confidence: 99%

Section: Analytic Dynamic Reconstructionmentioning

confidence: 99%

Algebraic and analytic reconstruction methods for dynamic tomography

Desbat

Rit

Clackdoyle³

et al. 2007

2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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show abstract

“…6,[15][16][17][18] Iterative MCR methods typically have large memory and computational requirements. Considering the additional computational burden, they are not suitable for our iterative ME-MCR.…”

Section: Introductionmentioning

confidence: 99%

“…19 Consequently, we chose an analytical method for our study. Several analytical MCR methods require motion models [15][16][17][18] but do not utilize the MVFs directly. Here, we adapted a motion tracking cone-beam backprojection method 6 which is efficient and can be easily implemented with MVFs.…”

Section: Introductionmentioning

confidence: 99%

A fully four-dimensional iterative motion estimation and compensation method for cardiac CT

et al. 2012

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Purpose: To develop a new fully four-dimensional (4D), iterative image reconstruction algorithm for cardiac CT that alternates the following two methods: estimation of a time-dependent motion vector field (MVF) of the heart from image data and reconstruction of images using the estimated MVF and projection data. Methods: Volumetric image data at different cardiac phase points were obtained using electrocardiogram-gated CT. Motion estimation (ME) and motion-compensated image reconstruction (MCR) were performed alternately until convergence was achieved. The ME method estimated the cardiac MVF using 4D nonrigid image registration between a cardiac reference phase and all the other phases. The nonrigid deformation of the heart was modeled using cubic B-splines. The cost function consisted of a sum of squared weighted differences and spatial and temporal regularization terms. A nested conjugate gradient optimization algorithm was applied to minimize the cost function and estimate the MVFs. Cardiac images were reconstructed using a motion-tracking algorithm that utilized the MVFs estimated by the ME method. The reconstructed images supplied the input to the ME of the next iteration. The performance of the proposed method was evaluated using four patient data sets acquired with a 64-slice CT scanner. The heart rates of the patients ranged from 52 to 71 beats/min. Results: Motion artifacts were significantly reduced, and the image quality increased with the number of iterations. Without MCR, the right coronary artery (RCA) was deformed into an arc in axial images of rapid phases. With the proposed method the RCA appeared sharper and was reconstructed similar in shape to the reconstruction at the quiescent phase at mid-diastole. The boundary between the interventricular septum and the right ventricle was also clearer and sharper using the proposed algorithm. The steepness of the transition range at a rapid phase (35% R-R) was increased from 6.8 HU/pixel to 11.5 HU/pixel. The ME-MCR algorithm converged in just four iterations. Conclusion:We developed a fully 4D image reconstruction method that alternates ME and MCR algorithms in an iterative fashion. Performance tests using clinical patient data resulted in reduced motion artifacts.

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“…This problem is still open and actively investigated. Currently proposed exact and analytic solutions are restricted to a limited class of deformations [17]- [19] which does not include the respiratory motion. Two solutions are therefore conceivable for analytic reconstruction: approximation of the respiratory motion by a deformation that can be exactly compensated for, or use of a heuristic solution [20]- [23].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Analytic and Algebraic Methods for Motion-Compensated Cone-Beam CT Reconstruction of the Thorax

Rit

Sarrut

Desbat

2009

IEEE Trans. Med. Imaging

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Abstract-Respiratory motion is a major concern in cone-beam (CB) computed tomography (CT) of the thorax. It causes artifacts such as blur, streaks, and bands, in particular when using slow-rotating scanners mounted on the gantry of linear accelerators. In this paper, we compare two approaches for motion-compensated CBCT reconstruction of the thorax. The first one is analytic; it is heuristically adapted from the method of Feldkamp, Davis, and Kress (FDK). The second one is algebraic: the system of linear equations is generated using a new algorithm for the projection of deformable volumes and solved using the Simultaneous Algebraic Reconstruction Technique (SART). For both methods, we propose to estimate the motion on patient data using a previously acquired 4-D CT image. The methods were tested on two digital and one mechanical motion-controlled phantoms and on a patient dataset. Our results indicate that the two methods correct most motion artifacts. However, the analytic method does not fully correct streaks and bands even if the motion is perfectly estimated due to the underlying approximation. In contrast, the algebraic method allows us full correction of respiratory-induced artifacts.

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Compensation of Some Time Dependent Deformations in Tomography

Cited by 46 publications

References 17 publications

Algebraic and analytic reconstruction methods for dynamic tomography

Algebraic and analytic reconstruction methods for dynamic tomography

A fully four-dimensional iterative motion estimation and compensation method for cardiac CT

Comparison of Analytic and Algebraic Methods for Motion-Compensated Cone-Beam CT Reconstruction of the Thorax

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