Improvement of cardiac CT reconstruction using local motion vector fields

Schirra, Carsten O.; Bontus, Claas; Stevendaal, Udo van; Dössel, Olaf; Graß, Michael

doi:10.1016/j.compmedimag.2008.10.012

Cited by 15 publications

(10 citation statements)

References 27 publications

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“…More recently, motion compensation methods 12 were investigated by several groups [13][14][15][16][17][18][19][20][21][22] to mitigate motion artifacts and effectively improve temporal resolution in cardiac CT imaging. The basic idea is to estimate the motion field from projection data or images available a priori.…”

Section: Ia Brief Review Of Methods To Improve Temporal Resolution mentioning

confidence: 99%

Temporal resolution improvement in cardiac CT using PICCS (TRI‐PICCS): Performance studies

Tang

Hsieh²,

Chen

2010

Medical Physics

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Section: Ia Brief Review Of Methods To Improve Temporal Resolution mentioning

confidence: 99%

Temporal resolution improvement in cardiac CT using PICCS (TRI‐PICCS): Performance studies

Tang

Hsieh²,

Chen

2010

Medical Physics

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“…In order to perform the experiments in cone beam geometry, a modification of the 3D Forbild phantom [31,37] was used. It was animated to simulate a beating heart.…”

Section: D Cone Beammentioning

confidence: 99%

Removing streak artifacts from ECG-gated reconstructions using deconvolution

Mory

Auvray

Zhang

et al. 2014

Journal of X-Ray Science and Technology

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BACKGROUND: 4D cardiac computed tomography aims at reconstructing the beating heart from a series of 2D projections and the simultaneously acquired electrocardiogram. Each cardiac phase is reconstructed by exploiting the subset of projections acquired during this particular cardiac phase only. In these conditions, the Feldkamp, Davis and Kress method (FDK) generates large streak artifacts in the reconstructed volumes, hampering the medical interpretation. These artifacts can be substantially reduced by deconvolution methods. OBJECTIVE: The aim of this paper is to compare two 4D cardiac CT reconstruction methods based on deconvolution, and to evaluate their practical benefits on two applications: cardiac micro CT and human cardiac C-arm CT. METHODS: The first evaluated method builds upon inverse filtering. It has been proposed recently and demonstrated on 4D cardiac micro CT. The second one is an iterative deconvolution method, and turns out equivalent to an ECG-gated Iterative Filtered Back Projection (ECG-gated IFBP). RESULTS: Results are presented on simulated data in 2D parallel beam, 2D fan beam and 3D cone beam geometries. CONCLUSIONS: Both methods are efficient on the cardiac micro CT simulations, but insufficient to handle 4D human cardiac C-Arm CT simulations. Overall, ECG-gated IFPB largely outperforms the inverse filtering method.

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“…Several quiescent phases were determined and used as reference phases, which is similar to what Schirra et al proposed. 10 In their approach, phase points from quiescent phases were grouped together into quiescent segments and one phase point from each segment was chosen as a reference phase. The 3D image registration was performed between each reference phase and all other phases in the same quiescent section and between all reference phases.…”

Section: Iiia Methodsmentioning

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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Improvement of cardiac CT reconstruction using local motion vector fields

Cited by 15 publications

References 27 publications

Temporal resolution improvement in cardiac CT using PICCS (TRI‐PICCS): Performance studies

Temporal resolution improvement in cardiac CT using PICCS (TRI‐PICCS): Performance studies

Removing streak artifacts from ECG-gated reconstructions using deconvolution

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

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