Temporally Targeted Imaging Method Applied to ECG-Gated Computed Tomography

Nett, Brian E.; Leng, Shuai; Zambelli, Joseph; Reeder, Scott B.; Speidel, Michael A.; Chen, Guang Hong

doi:10.1016/j.acra.2007.07.003

Cited by 6 publications

(7 citation statements)

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“…[23][24][25][26][27][28][29][30][31][32] In these methods, one of the most important features is that they enable accurate image reconstruction of a local region of interest ͑ROI͒ using projection data acquired from an angular range which is shorter than 180°plus the fan angle. These new algorithms indeed enable improvement of temporal resolution 33,34 for some peripheral ROIs. If one wants to use this method to achieve a factor of 2 improvement in temporal resolution, the available angular range is only about 120°.…”

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

confidence: 94%

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: 94%

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

Tang

Hsieh²,

Chen

2010

Medical Physics

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“…The 2D sufficiency condition is similar to Tuy's condition [4] for 3D exact reconstruction, in that any line which can be drawn through the ROI must intersect the source trajectory at least once. This condition can be exploited to reduce the temporal window of acquisition for off-center ROI imaging [30,31].…”

Section: Cone-beam Step-and-shoot Reconstructionmentioning

confidence: 99%

Recent Advances in CT Image Reconstruction

et al. 2013

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Over the past two decades, rapid system and hardware development of x-ray computed tomography (CT) technologies has been accompanied by equally exciting advances in image reconstruction algorithms. The algorithmic development can generally be classified into three major areas: analytical reconstruction, model-based iterative reconstruction, and application-specific reconstruction. Given the limited scope of this chapter, it is nearly impossible to cover every important development in this field; it is equally difficult to provide sufficient breadth and depth on each selected topic. As a compromise, we have decided, for a selected few topics, to provide sufficient high-level technical descriptions and to discuss their advantages and applications.

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“…In these equations,  denotes the Kronecker direct product operation,ê τ = (0,0,...,0,1 τ ,0,...,0) tr is the τth standard column basis in a T dimensional space, I T is the T × T identity matrix, and vec(X) is the vectorization operation of the spatial-temporal matrix introduced in Eq. (6). Note that the dimension of the column vector ⃗ Y is N and the dimension of the column vector ⃗ y τ for an individual time frame is N/T.…”

Section: C Forward Model Of the Spatial-temporal Image Matrixmentioning

confidence: 99%

“…(6). Note that the dimension of the column vector ⃗ Y is N and the dimension of the column vector ⃗ y τ for an individual time frame is N/T.…”

Section: C Forward Model Of the Spatial-temporal Image Matrixmentioning

confidence: 99%

“…1 and references therein) or model based iterative image reconstruction methods. [2][3][4][5] Many of these new reconstruction methods have been directly exploited to either improve temporal resolution 6,7 or reduce radiation dose. 8 Regarding the reconstruction of a static image object using an analytical reconstruction method, the Tuy data sufficiency condition 9 is of fundamental importance.…”

Section: Introductionmentioning

confidence: 99%

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Synchronized multiartifact reduction with tomographic reconstruction (SMART‐RECON): A statistical model based iterative image reconstruction method to eliminate limited‐view artifacts and to mitigate the temporal‐average artifacts in time‐resolved CT

Chen

2015

Medical Physics

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Purpose: In x-ray computed tomography (CT), a violation of the Tuy data sufficiency condition leads to limited-view artifacts. In some applications, it is desirable to use data corresponding to a narrow temporal window to reconstruct images with reduced temporal-average artifacts. However, the need to reduce temporal-average artifacts in practice may result in a violation of the Tuy condition and thus undesirable limited-view artifacts. In this paper, the authors present a new iterative reconstruction method, synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON), to eliminate limited-view artifacts using data acquired within an ultranarrow temporal window that severely violates the Tuy condition. Methods: In time-resolved contrast enhanced CT acquisitions, image contrast dynamically changes during data acquisition. Each image reconstructed from data acquired in a given temporal window represents one time frame and can be denoted as an image vector. Conventionally, each individual time frame is reconstructed independently. In this paper, all image frames are grouped into a spatial-temporal image matrix and are reconstructed together. Rather than the spatial and/or temporal smoothing regularizers commonly used in iterative image reconstruction, the nuclear norm of the spatial-temporal image matrix is used in SMART-RECON to regularize the reconstruction of all image time frames. This regularizer exploits the low-dimensional structure of the spatial-temporal image matrix to mitigate limited-view artifacts when an ultranarrow temporal window is desired in some applications to reduce temporal-average artifacts. Both numerical simulations in two dimensional image slices with known ground truth and in vivo human subject data acquired in a contrast enhanced cone beam CT exam have been used to validate the proposed SMART-RECON algorithm and to demonstrate the initial performance of the algorithm. Reconstruction errors and temporal fidelity of the reconstructed images were quantified using the relative root mean square error (rRMSE) and the universal quality index (UQI) in numerical simulations. The performance of the SMART-RECON algorithm was compared with that of the prior image constrained compressed sensing (PICCS) reconstruction quantitatively in simulations and qualitatively in human subject exam. Results: In numerical simulations, the 240• short scan angular span was divided into four consecutive 60• angular subsectors. SMART-RECON enables four high temporal fidelity images without limitedview artifacts. The average rRMSE is 16% and UQIs are 0.96 and 0.95 for the two local regions of interest, respectively. In contrast, the corresponding average rRMSE and UQIs are 25%, 0.78, and 0.81, respectively, for the PICCS reconstruction. Note that only one filtered backprojection image can be reconstructed from the same data set with an average rRMSE and UQIs are 45%, 0.71, and 0.79, respectively, to benchmark reconstruction accuracies. For in vivo contrast enhanced cone beam CT data acquired from...

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Temporally Targeted Imaging Method Applied to ECG-Gated Computed Tomography

Cited by 6 publications

References 38 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

Recent Advances in CT Image Reconstruction

Synchronized multiartifact reduction with tomographic reconstruction (SMART‐RECON): A statistical model based iterative image reconstruction method to eliminate limited‐view artifacts and to mitigate the temporal‐average artifacts in time‐resolved CT

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