Multi-dimensional tensor-based adaptive filter (TBAF) for low dose x-ray CT

Knaup, Michael; Lebedev, Sergej; Sawall, Stefan; Kachelrieß, Marc

doi:10.1117/12.2081910

Cited by 3 publications

(4 citation statements)

References 2 publications

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“…Data postprocessing. Given the fact that the motion compensation results in an image quality equivalent to a standard reconstruction in terms of image noise, we apply an anisotropic multi-dimensional adaptive tensor-based filter (TBAF) to the volumes in a postprocessing step 37 . In brief, this filter computes a local orientation tensor, estimates Eigenvectors and Eigenvalues of this tensor and filters in the direction corresponding to the largest Eigenvalue while adapting the filter strength to local noise properties.…”

Section: Methodsmentioning

confidence: 99%

Coronary micro-computed tomography angiography in mice

Sawall

Beckendorf

Amato

et al. 2020

Sci Rep

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Coronary computed tomography angiography is an established technique in clinical practice and a valuable tool in the diagnosis of coronary artery disease in humans. Imaging of coronaries in preclinical research, i.e. in small animals, is very difficult due to the high demands on spatial and temporal resolution. Mice exhibit heart rates of up to 600 beats per minute motivating the need for highest detector framerates while the coronaries show diameters below 100 μm indicating the requirement for highest spatial resolution. We herein use a custom built micro–CT equipped with dedicated reconstruction algorithms to illustrate that coronary imaging in mice is possible. The scanner provides a spatial and temporal resolution sufficient for imaging of smallest, moving anatomical structures and the dedicated reconstruction algorithms reduced radiation dose to less than 1 Gy but do not yet allow for longitudinal studies. Imaging studies were performed in ten mice administered with a blood-pool contrast agent. Results show that the course of the left coronary artery can be visualized in all mice and all major branches can be identified for the first time using micro-CT. This reduces the gap in cardiac imaging between clinical practice and preclinical research.

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Section: Methodsmentioning

confidence: 99%

Coronary micro-computed tomography angiography in mice

Sawall

Beckendorf

Amato

et al. 2020

Sci Rep

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“…By contrast, backprojection suggests a large number of weak but "possible" non-zero density "peaks." For a comparison of "back-projection," see Badea & Gordon and Knaup et al, (2015)[3939]. However, combining several "backmultiplications" without further processing produces blurred images, similar to unfiltered backprojection.…”

Section: The New Ment Estimation Structure For Tomographic Reconstruc...mentioning

confidence: 99%

Non-Linear Extended Filter with Near Unit-Gain Feedback Loop Yields High Quality, Fast MENT CT Reconstruction

Jarisch¹

2023

Preprint

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<p>High-quality, fast 3D tomographic reconstruction of objects from projections remains challenging, especially in noisy, sparse, and high contrast measurement environments. Current linear and non-linear iterative processing methods are limited in their ability to extract diagnostic information. To improve information extraction, we propose a new object density estimator with near-unity feedback loop gain, called extended High Efficiency CT with Optimized Recursions (eHECTOR). This algorithm converges to the maximum entropy (MENT) voxel estimator with non-linear transformations. An iterated small signal linearized extended filter with near-unit filtered back-projection (FBP) loop gain refines the object density estimate while increasing resolution. This new model requires little code, reduces data manipulation, and improves accuracy and speed of convergence. Every iteration through the non-linear filter provides effective error minimization in all voxel degrees of freedom of the high-dimensional voxel state space. The proposed method overcomes limitations of current state-of-the-art non-linear reconstruction, which is limited to low-dimensional subspace error contraction, thus limiting the rate of convergence in the high-dimensional voxel space. The proposed method provides improved information extraction, numerical stability, and efficient use of computational resources while minimizing numerical errors and noise sensitivity. It has broad clinical and industrial applications due to its efficiency, accuracy, and high speed. It allows for reduced radiation, smaller X-ray spot size, concurrent modeling of movement, and system calibration while reducing noise, image blur, and artifacts.</p>

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“…Supplemental data acquisition and reconstruction parameters for the figures presented in this and future sections are included in Table 3. refs: [10][11][12][13][14][15][16] CT is one of the principal modalities used for diagnosing lung pathology and has become increasingly important for diagnosing virusinduced lung infections during the COVID-19 pandemic. In translational efforts, micro-CT has been used for preclinical research toward finding an efficient vaccine and antiviral drugs against COVID-19.…”

Section: Applications Of Modern Micro-ct Imagingmentioning

confidence: 99%

“…GPUs) and software now enable simultaneous IR of temporal and spectral x-ray CT data sets spanning multiple volumes (multiple phases and/or energies). For instance, multi-channel regularization such as patch-based singular value thresholding [65], rank-sparse kernel regression [12], oriented filtering [11], and deformable image registration [10] exploit prior knowledge of data structure to dramatically improve the fidelity of reconstructed images. These data regularizers are often incorporated as "plug-and-play" regularizers within robust algebraic reconstruction frameworks such as the Alternating Direction Method of Multipliers (ADMM) and the split Bregman method [66,67].…”

Section: Reconstruction Of Ct Datamentioning

confidence: 99%

Advances in micro-CT imaging of small animals

Clark

Badea

2021

Physica Medica

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Micron-scale computed tomography (micro-CT) imaging is a ubiquitous, cost-effective, and non-invasive three-dimensional imaging modality. We review recent developments and applications of micro-CT for preclinical research. Methods: Based on a comprehensive review of recent micro-CT literature, we summarize features of state-of-theart hardware and ongoing challenges and promising research directions in the field. Results: Representative features of commercially available micro-CT scanners and some new applications for both in vivo and ex vivo imaging are described. New advancements include spectral scanning using dual-energy micro-CT based on energy-integrating detectors or a new generation of photon-counting x-ray detectors (PCDs). Beyond two-material discrimination, PCDs enable quantitative differentiation of intrinsic tissues from one or more extrinsic contrast agents. When these extrinsic contrast agents are incorporated into a nanoparticle platform (e.g. liposomes), novel micro-CT imaging applications are possible such as combined therapy and diagnostic imaging in the field of cancer theranostics. Another major area of research in micro-CT is in x-ray phase contrast (XPC) imaging. XPC imaging opens CT to many new imaging applications because phase changes are more sensitive to density variations in soft tissues than standard absorption imaging. We further review the impact of deep learning on micro-CT. We feature several recent works which have successfully applied deep learning to micro-CT data, and we outline several challenges specific to micro-CT. Conclusions: All of these advancements establish micro-CT imaging at the forefront of preclinical research, able to provide anatomical, functional, and even molecular information while serving as a testbench for translational research.

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Multi-dimensional tensor-based adaptive filter (TBAF) for low dose x-ray CT

Cited by 3 publications

References 2 publications

Coronary micro-computed tomography angiography in mice

Coronary micro-computed tomography angiography in mice

Non-Linear Extended Filter with Near Unit-Gain Feedback Loop Yields High Quality, Fast MENT CT Reconstruction

Advances in micro-CT imaging of small animals

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