The Experts below are selected from a list of 21108 Experts worldwide ranked by ideXlab platform
Marcus Brehm - One of the best experts on this subject based on the ideXlab platform.
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Cardiorespiratory motion-compensated micro-CT image reconstruction using an Artifact Model-based motion estimation.
Medical physics, 2015Co-Authors: Marcus Brehm, Stefan Sawall, Joscha Maier, Sebastian Sauppe, Marc KachelrießAbstract:Purpose: Cardiac in vivo micro-CT imaging of small animals typically requires double gating due to long scan times and high respiratory rates. The simultaneous respiratory and cardiac gating can either be done prospectively or retrospectively. In any case, for true 5D imaging, i.e., three spatial dimensions plus one respiratory-temporal dimension plus one cardiac temporal dimension, the amount of information corresponding to a given respiratory and cardiac phase is orders of magnitude lower than the total amount of information acquired. Achieving similar image quality for 5D than for usual 3D investigations would require increasing the amount of data and thus the applied dose to the animal. Therefore, the goal is phase-correlated imaging with high image quality but without increasing the dose level. Methods: To achieve this, the authors propose a new image reconstruction algorithm that makes use of all available projection data, also of that corresponding to other motion windows. In particular, the authors apply a motion-compensated image reconstruction approach that sequentially compensates for respiratory and cardiac motion to decrease the impact of sparsification. In that process, all projection data are used no matter which motion phase they were acquired in. Respiratory and cardiac motion are compensated for by using motion vector fields. These motion vector fields are estimated from initial phase-correlated reconstructions based on a deformable registration approach. To decrease the sensitivity of the registration to sparse-view Artifacts, an Artifact Model-based approach is used including a cyclic consistent nonrigid registration algorithm. Results: The preliminary results indicate that the authors’ approach removes the sparse-view Artifacts of conventional phase-correlated reconstructions while maintaining temporal resolution. In addition, it achieves noise levels and spatial resolution comparable to that of nongated reconstructions due to the improved dose usage. By using the proposed motion estimation, no sensitivity to streaking Artifacts has been observed. Conclusions: Using sequential double gating combined with Artifact Model-based motion estimation allows to accurately estimate respiratory and cardiac motion from highly undersampled data. No sensitivity to streaking Artifacts introduced by sparse angular sampling has been observed for the investigated dose levels. The motion-compensated image reconstruction was able to correct for both, respiratory and cardiac motion, by applying the estimated motion vector fields. The administered dose per animal can thus be reduced for 5D imaging allowing for longitudinal studies at the highest image quality.
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Artifact Model based respiratory motion compensation moco for simultaneous pet mr based on strongly undersampled radial mr data
Nuclear Science Symposium and Medical Imaging Conference, 2014Co-Authors: Christopher M Rank, Marcus Brehm, Thorsten Heuber, Marc KachelriebAbstract:We propose a new method for PET/MR respiratory motion compensation, which is based on strongly undersampled MR data. In our simulation study, we applied a 3D encoded radial stack-of-stars sampling scheme with 160 radial spokes per slice and an acquisition time of 38 s for MR data acquisition. Based on gated but strongly undersampled and thus streak Artifact-contaminated 4D MR images, high-fidelity motion vector fields were estimated applying our newly-developed Artifact Model-based registration framework. Subsequently, MoCo 4D PET images of a simulated breathing thorax were reconstructed. Evaluation of eight artificial hot lesions in the lungs and upper abdomen showed a significant visual as well as a quantitative improvement in terms of SUVmean values, lesion size and localization for MoCo 4D PET images compared to 3D and 4D gated reconstructions especially for small lesion sizes.
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Artifact Model-based respiratory motion compensation (MoCo) for simultaneous PET/MR based on strongly undersampled radial MR data
2014 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS MIC), 2014Co-Authors: Christopher M Rank, Marcus Brehm, Thorsten Heuber, Marc KachelriebAbstract:We propose a new method for PET/MR respiratory motion compensation, which is based on strongly undersampled MR data. In our simulation study, we applied a 3D encoded radial stack-of-stars sampling scheme with 160 radial spokes per slice and an acquisition time of 38 s for MR data acquisition. Based on gated but strongly undersampled and thus streak Artifact-contaminated 4D MR images, high-fidelity motion vector fields were estimated applying our newly-developed Artifact Model-based registration framework. Subsequently, MoCo 4D PET images of a simulated breathing thorax were reconstructed. Evaluation of eight artificial hot lesions in the lungs and upper abdomen showed a significant visual as well as a quantitative improvement in terms of SUVmean values, lesion size and localization for MoCo 4D PET images compared to 3D and 4D gated reconstructions especially for small lesion sizes.
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Artifact-resistant motion estimation with a patient-specific Artifact Model for motion-compensated cone-beam CT.
Medical physics, 2013Co-Authors: Marcus Brehm, Pascal Paysan, Markus Oelhafen, Marc KachelrießAbstract:Purpose: In image-guided radiation therapy (IGRT) valuable information for patient positioning, dose verification, and adaptive treatment planning is provided by an additional kV imaging unit. However, due to the limited gantry rotation speed during treatment the typical acquisition time is quite long. Tomographic images of the thorax suffer from motion blurring or, if a gated 4D reconstruction is performed, from significant streak Artifacts. Our purpose is to provide a method that reliably estimates respiratory motion in presence of severe Artifacts. The estimated motion vector fields are then used for motion-compensated image reconstruction to provide high quality respiratory-correlated 4D volumes for on-board cone-beam CT (CBCT) scans. Methods: The proposed motion estimation method consists of a Model that explicitly addresses image Artifacts because in presence of severe Artifacts state-of-the-art registration methods tend to register Artifacts rather than anatomy. Our Artifact Model, e.g., generates streak Artifacts very similar to those included in the gated 4D CBCT images, but it does not include respiratory motion. In combination with a registration strategy, the Model gives an error estimate that is used to compensate the corresponding errors of the motion vector fields that are estimated from the gated 4D CBCT images. The algorithm is tested in combination with a cyclic registration approach using temporal constraints and with a standard 3D–3D registration approach. A qualitative and quantitative evaluation of the motion-compensated results was performed using simulated rawdata created on basis of clinical CT data. Further evaluation includes patient data which were scanned with an on-board CBCT system. Results: The Model-based motion estimation method is nearly insensitive to image Artifacts of gated 4D reconstructions as they are caused by angular undersampling. The motion is accurately estimated and our motion-compensated image reconstruction algorithm can correct for it. Motion Artifacts of 3D standard reconstruction are significantly reduced, while almost no new Artifacts are introduced. Conclusions: Using the Artifact Model allows to accurately estimate and compensate for patient motion, even if the initial reconstructions are of very low image quality. Using our approach together with a cyclic registration algorithm yields a combination which shows almost no sensitivity to sparse-view Artifacts and thus ensures both high spatial and high temporal resolution.
Marc Kachelrieß - One of the best experts on this subject based on the ideXlab platform.
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Cardiorespiratory motion-compensated micro-CT image reconstruction using an Artifact Model-based motion estimation.
Medical physics, 2015Co-Authors: Marcus Brehm, Stefan Sawall, Joscha Maier, Sebastian Sauppe, Marc KachelrießAbstract:Purpose: Cardiac in vivo micro-CT imaging of small animals typically requires double gating due to long scan times and high respiratory rates. The simultaneous respiratory and cardiac gating can either be done prospectively or retrospectively. In any case, for true 5D imaging, i.e., three spatial dimensions plus one respiratory-temporal dimension plus one cardiac temporal dimension, the amount of information corresponding to a given respiratory and cardiac phase is orders of magnitude lower than the total amount of information acquired. Achieving similar image quality for 5D than for usual 3D investigations would require increasing the amount of data and thus the applied dose to the animal. Therefore, the goal is phase-correlated imaging with high image quality but without increasing the dose level. Methods: To achieve this, the authors propose a new image reconstruction algorithm that makes use of all available projection data, also of that corresponding to other motion windows. In particular, the authors apply a motion-compensated image reconstruction approach that sequentially compensates for respiratory and cardiac motion to decrease the impact of sparsification. In that process, all projection data are used no matter which motion phase they were acquired in. Respiratory and cardiac motion are compensated for by using motion vector fields. These motion vector fields are estimated from initial phase-correlated reconstructions based on a deformable registration approach. To decrease the sensitivity of the registration to sparse-view Artifacts, an Artifact Model-based approach is used including a cyclic consistent nonrigid registration algorithm. Results: The preliminary results indicate that the authors’ approach removes the sparse-view Artifacts of conventional phase-correlated reconstructions while maintaining temporal resolution. In addition, it achieves noise levels and spatial resolution comparable to that of nongated reconstructions due to the improved dose usage. By using the proposed motion estimation, no sensitivity to streaking Artifacts has been observed. Conclusions: Using sequential double gating combined with Artifact Model-based motion estimation allows to accurately estimate respiratory and cardiac motion from highly undersampled data. No sensitivity to streaking Artifacts introduced by sparse angular sampling has been observed for the investigated dose levels. The motion-compensated image reconstruction was able to correct for both, respiratory and cardiac motion, by applying the estimated motion vector fields. The administered dose per animal can thus be reduced for 5D imaging allowing for longitudinal studies at the highest image quality.
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Artifact-resistant motion estimation with a patient-specific Artifact Model for motion-compensated cone-beam CT.
Medical physics, 2013Co-Authors: Marcus Brehm, Pascal Paysan, Markus Oelhafen, Marc KachelrießAbstract:Purpose: In image-guided radiation therapy (IGRT) valuable information for patient positioning, dose verification, and adaptive treatment planning is provided by an additional kV imaging unit. However, due to the limited gantry rotation speed during treatment the typical acquisition time is quite long. Tomographic images of the thorax suffer from motion blurring or, if a gated 4D reconstruction is performed, from significant streak Artifacts. Our purpose is to provide a method that reliably estimates respiratory motion in presence of severe Artifacts. The estimated motion vector fields are then used for motion-compensated image reconstruction to provide high quality respiratory-correlated 4D volumes for on-board cone-beam CT (CBCT) scans. Methods: The proposed motion estimation method consists of a Model that explicitly addresses image Artifacts because in presence of severe Artifacts state-of-the-art registration methods tend to register Artifacts rather than anatomy. Our Artifact Model, e.g., generates streak Artifacts very similar to those included in the gated 4D CBCT images, but it does not include respiratory motion. In combination with a registration strategy, the Model gives an error estimate that is used to compensate the corresponding errors of the motion vector fields that are estimated from the gated 4D CBCT images. The algorithm is tested in combination with a cyclic registration approach using temporal constraints and with a standard 3D–3D registration approach. A qualitative and quantitative evaluation of the motion-compensated results was performed using simulated rawdata created on basis of clinical CT data. Further evaluation includes patient data which were scanned with an on-board CBCT system. Results: The Model-based motion estimation method is nearly insensitive to image Artifacts of gated 4D reconstructions as they are caused by angular undersampling. The motion is accurately estimated and our motion-compensated image reconstruction algorithm can correct for it. Motion Artifacts of 3D standard reconstruction are significantly reduced, while almost no new Artifacts are introduced. Conclusions: Using the Artifact Model allows to accurately estimate and compensate for patient motion, even if the initial reconstructions are of very low image quality. Using our approach together with a cyclic registration algorithm yields a combination which shows almost no sensitivity to sparse-view Artifacts and thus ensures both high spatial and high temporal resolution.
Marc Kachelrieb - One of the best experts on this subject based on the ideXlab platform.
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Artifact Model based respiratory motion compensation moco for simultaneous pet mr based on strongly undersampled radial mr data
Nuclear Science Symposium and Medical Imaging Conference, 2014Co-Authors: Christopher M Rank, Marcus Brehm, Thorsten Heuber, Marc KachelriebAbstract:We propose a new method for PET/MR respiratory motion compensation, which is based on strongly undersampled MR data. In our simulation study, we applied a 3D encoded radial stack-of-stars sampling scheme with 160 radial spokes per slice and an acquisition time of 38 s for MR data acquisition. Based on gated but strongly undersampled and thus streak Artifact-contaminated 4D MR images, high-fidelity motion vector fields were estimated applying our newly-developed Artifact Model-based registration framework. Subsequently, MoCo 4D PET images of a simulated breathing thorax were reconstructed. Evaluation of eight artificial hot lesions in the lungs and upper abdomen showed a significant visual as well as a quantitative improvement in terms of SUVmean values, lesion size and localization for MoCo 4D PET images compared to 3D and 4D gated reconstructions especially for small lesion sizes.
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Artifact Model-based respiratory motion compensation (MoCo) for simultaneous PET/MR based on strongly undersampled radial MR data
2014 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS MIC), 2014Co-Authors: Christopher M Rank, Marcus Brehm, Thorsten Heuber, Marc KachelriebAbstract:We propose a new method for PET/MR respiratory motion compensation, which is based on strongly undersampled MR data. In our simulation study, we applied a 3D encoded radial stack-of-stars sampling scheme with 160 radial spokes per slice and an acquisition time of 38 s for MR data acquisition. Based on gated but strongly undersampled and thus streak Artifact-contaminated 4D MR images, high-fidelity motion vector fields were estimated applying our newly-developed Artifact Model-based registration framework. Subsequently, MoCo 4D PET images of a simulated breathing thorax were reconstructed. Evaluation of eight artificial hot lesions in the lungs and upper abdomen showed a significant visual as well as a quantitative improvement in terms of SUVmean values, lesion size and localization for MoCo 4D PET images compared to 3D and 4D gated reconstructions especially for small lesion sizes.
Orazio Gambino - One of the best experts on this subject based on the ideXlab platform.
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Bias Artifact suppression on MR volumes
Computer methods and programs in biomedicine, 2008Co-Authors: Edoardo Ardizzone, Roberto Pirrone, Orazio GambinoAbstract:RF-inhomogeneity correction is a relevant research topic in the field of magnetic resonance imaging (MRI). A volume corrupted by this Artifact exhibits nonuniform illumination both inside a single slice and between adjacent ones. In this work a bias correction technique is presented, which suppresses this Artifact on MR volumes scanned from different body parts without any a priori hypothesis on the Artifact Model. Theoretical foundations of the method are reported together with experimental results and a comparison is presented with both the 2D version of the algorithm and other techniques that are widely used in MRI literature.
Clemensnylandsted Klokmose - One of the best experts on this subject based on the ideXlab platform.
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the human Artifact Model an activity theoretical approach to Artifact ecologies
Human-Computer Interaction, 2013Co-Authors: Susanne B Dker, Clemensnylandsted KlokmoseAbstract:Artifacts and their use are constantly developing, and we address development in, and of, use. The framework needs to support such development through concepts and methods. This leads to a methodological approach that focuses on new Artifacts to supplement and substitute existing Artifacts. Through a design case, we develop the methodological approach and illustrate how the human–Artifact Model can be applied to analyze present Artifacts and to design future ones. The Model is used to structure such analysis and to reason about findings while providing leverage from activity theoretical insights on mediation, dialectics, and levels of activity.
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The Human–Artifact Model: An Activity Theoretical Approach to Artifact Ecologies
Human–Computer Interaction, 2011Co-Authors: Susanne B⊘dker, Clemensnylandsted KlokmoseAbstract:Artifacts and their use are constantly developing, and we address development in, and of, use. The framework needs to support such development through concepts and methods. This leads to a methodological approach that focuses on new Artifacts to supplement and substitute existing Artifacts. Through a design case, we develop the methodological approach and illustrate how the human–Artifact Model can be applied to analyze present Artifacts and to design future ones. The Model is used to structure such analysis and to reason about findings while providing leverage from activity theoretical insights on mediation, dialectics, and levels of activity.
