The Experts below are selected from a list of 2268 Experts worldwide ranked by ideXlab platform
Daniel K Sodickson - One of the best experts on this subject based on the ideXlab platform.
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comprehensive quantification of signal to noise ratio and g factor for image based and k space based parallel imaging reconstructions
Magnetic Resonance in Medicine, 2008Co-Authors: Philip M Robson, Daniel K Sodickson, Aaron K Grant, Ananth J Madhuranthakam, Riccardo Lattanzi, Charles A MckenzieAbstract:Parallel imaging approaches are widely used for accelerating MR image acquisitions (Simultaneous Acquisition of Spatial Harmonics (SMASH) (1), Sensitivity Encoding (SENSE) (2), Generalized Auto-Calibrating Partially Parallel Acquisition (GRAPPA) (3). Receiving signals simultaneously in the independent elements of a Radiofrequency Coil array allows acquisition of some of the phase-encoded signals to be omitted. The distinct spatial sensitivity profiles of the elements contain spatial information that may be used for the purpose of spatial encoding in the image that is normally provided by application of magnetic field gradients. The penalty for acquiring fewer signals is a loss of Signal-to-Noise Ratio (SNR) in the final image by a factor of the square root of the acceleration factor √R due to reduced signal averaging. In parallel imaging image-noise is further amplified by the ill-conditioning of the image reconstruction process. In general, the noise amplification is spatially variant and depends on the specific geometry of the Radiofrequency Coil array used and is therefore characterized by the (geometry) g-factor (2). An accurate and quantitative method of analyzing noise amplification is essential for objective comparison between parallel imaging techniques and between image reconstruction methods when developing new methods and designing clinical imaging protocols. Spatial variation of the image noise precludes the conventional (and simple) Region-of-Interest (ROI) approach for SNR estimation which uses a region of signal within the object and a region of noise outside of the object (4,5), making SNR difficult to deal with practically in parallel imaging. Quantification of noise amplification in parallel imaging has been studied previously (2,6), producing methods for direct calculation of image noise, g-factor (2) and SNR (7) for some classes of parallel imaging strategies. However, all existing techniques are subject to certain regimes in which it is impossible to calculate SNR analytically. Direct image noise matrix approaches (2) require memory for matrices of size O(n2), where n may be as large as N2 for arbitrary k-space trajectories and generalized SENSE image reconstruction (8), where N is the image matrix dimension. Typically N may be 256, which, for complex floating-point data, leads to a reconstruction matrix of approximately 30 Gb. For direct GRAPPA approaches n may be as large as N3 (9) leading to a reconstruction matrix of approximately 2000 Tb. Furthermore, matrix inversion approaches require O(n3) operations (8). Thus, direct computation rapidly may become intractable such that currently there is no universal approach for measuring SNR or g-factor. Statistical methods, for example Monte Carlo and bootstrapping methods (10), are often used in functional parameter estimation from MRI (e.g., Jones and Steger et al.) (11,12). This work develops a simple Monte Carlo method for rigorously calculating image noise propagating through the image reconstruction itself (similarly to methods explored previously) (13,14). This method allows calculation of SNR and g-factor for all parallel imaging techniques which use a linear image reconstruction algorithm, irrespective of whether direct calculation is available or computationally tractable. In this work we demonstrate noise analysis for two classes of parallel imaging methods (SENSE and GRAPPA) routinely used in clinical imaging applications.
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parallel magnetic resonance imaging with adaptive radius in k space pars constrained image reconstruction using k space locality in Radiofrequency Coil encoded data
Magnetic Resonance in Medicine, 2005Co-Authors: Daniel K Sodickson, Charles A Mckenzie, Ernest N Yeh, Michael A OhligerAbstract:A parallel image reconstruction algorithm is presented that exploits the k-space locality in Radiofrequency (RF) Coil encoded data. In RF Coil encoding, information relevant to reconstructing an omitted datum rapidly diminishes as a function of k-space separation between the omitted datum and the acquired signal data. The proposed method, parallel magnetic resonance imaging with adaptive radius in k-space (PARS), harnesses this physical property of RF Coil encoding via a sliding-kernel approach. Unlike generalized parallel imaging approaches that might typically involve inverting a prohibitively large matrix for arbitrary sampling trajectories, the PARS sliding-kernel approach creates manageable and distributable independent matrices to be inverted, achieving both computational efficiency and numerical stability. An empirical method designed to measure total error power is described, and the total error power of PARS reconstructions is studied over a range of k-space radii and accelerations, revealing "minimal-error" conditions at comparatively modest k-space radii. PARS reconstructions of undersampled in vivo Cartesian and non-Cartesian data sets are shown and are compared selectively with traditional SENSE reconstructions. Various characteristics of the PARS k-space locality constraint (such as the tradeoff between signal-to-noise ratio and artifact power and the relationship with iterative parallel conjugate gradient approaches or nonparallel gridding approaches) are discussed.
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smash imaging with an eight element multiplexed rf Coil array
Magnetic Resonance Materials in Physics Biology and Medicine, 2000Co-Authors: James A Bankson, Mark A Griswold, Steven M Wright, Daniel K SodicksonAbstract:SMASH (SiMultaneous Acquisition of Spatial Harmonics) is a technique which can be used to acquire multiple lines ofk-space in parallel, by using spatial information from a Radiofrequency Coil array to perform some of the encoding normally produced by gradients. Using SMASH, imaging speed can be increased up to a maximum acceleration factor equal to the number of Coil array elements. This work is a feasibility study which examines the use of SMASH with specialized Coil array and data reception hardware to achieve previously unattainable accelerations. An eight element linear SMASH array was designed to operate in conjunction with a time domain multiplexing system to examine the effectiveness of SMASH imaging with as much as eightfold acceleration factors. Time domain multiplexing allowed the multiple independent array elements to be sampled through a standard single-channel receiver. SMASH-reconstructed images using this system were compared with reference images, and signal to noise ratio and reconstruction artifact power were measured as a function of acceleration factor. Results of the imaging experiments showed an almost constant SNR for SMASH acceleration factors of up to eight. Artifact power remained low within this range of acceleration factors. This study demonstrates that efficient SMASH imaging at high acceleration factors is feasible using appropriate hardware, and that time domain multiplexing is a convenient strategy to provide the multiple channels required for rapid imaging with large arrays.
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signal to noise ratio and signal to noise efficiency in smash imaging
Magnetic Resonance in Medicine, 1999Co-Authors: Daniel K Sodickson, Peter M Jakob, Mark A Griswold, Robert R Edelman, Warren J ManningAbstract:A general theory of signal-to-noise ratio (SNR) in simultaneous acquisition of spatial harmonics (SMASH) imaging is presented, and the predictions of the theory are verified in imaging experiments and in numerical simulations. In a SMASH image, multiple lines of k-space are generated simultaneously through combinations of magnetic resonance signals in a Radiofrequency Coil array. Here, effects of noise correlations between array elements as well as new correlations introduced by the SMASH reconstruction procedure are assessed. SNR and SNR efficiency in SMASH images are compared with results using traditional array combination strategies. Under optimized conditions, SMASH achieves the same average SNR efficiency as ideal pixel-by-pixel array combinations, while allowing imaging to proceed at otherwise unattainable speeds. The k-space nature of SMASH reconstructions can lead to oscillatory spatial variations in noise standard deviation, which can produce local enhancements of SNR in particular regions.
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accelerated cardiac imaging using the smash technique
Journal of Cardiovascular Magnetic Resonance, 1999Co-Authors: Peter M Jakob, Mark A Griswold, Robert R Edelman, Warren J Manning, Daniel K SodicksonAbstract:SMASH (SiMultaneous Acquisition of Spatial Harmonics) was recently introduced as a novel rapid-imaging technique. The SMASH technique uses a partially parallel acquisition strategy, using spatial information from a Radiofrequency Coil array to accelerate imaging. This study constitutes the first application of SMASH to cardiac magnetic resonance imaging. The increased imaging speed provided by SMASH was used to obtain images with reduced breathhold duration, enhanced spatial resolution, and increased temporal resolution in healthy volunteers. The results obtained demonstrate the feasibility and potential clinical utility of cardiac magnetic resonance imaging using the SMASH technique.
Gregory A Sorensen - One of the best experts on this subject based on the ideXlab platform.
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toward implementing an mri based pet attenuation correction method for neurologic studies on the mr pet brain prototype
The Journal of Nuclear Medicine, 2010Co-Authors: Ciprian Catana, Andre J W Van Der Kouwe, Thomas Benner, Christian Michel, Michael Hamm, Matthias Fenchel, Bruce Fischl, Bruce R Rosen, Matthias J Schmand, Gregory A SorensenAbstract:UNLABELLED: Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. METHODS: The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the Radiofrequency Coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. RESULTS: Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm(-1) to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the Radiofrequency Coil attenuation can cause large underestimations (i.e.,
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toward implementing an mri based pet attenuation correction method for neurologic studies on the mr pet brain prototype
The Journal of Nuclear Medicine, 2010Co-Authors: Ciprian Catana, Thomas Benner, Christian Michel, Michael Hamm, Matthias Fenchel, Bruce Fischl, Bruce R Rosen, Matthias J Schmand, Andre J W Van Der Kouwe, Gregory A SorensenAbstract:Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. Methods: The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the Radiofrequency Coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. Results: Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm -1 to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the Radiofrequency Coil attenuation can cause large underestimations (i.e., ≤50%) in the reconstructed images. Furthermore, the Coil location in the PET field of view has to be accurately known. High-quality bone-air segmentation can be performed using the DUTE data. The PET images obtained using the DUTE MRI- and CT-based AC methods compare favorably in most of the brain structures. Conclusion: A DUTE MRI-based AC method considering all these factors was implemented. Preliminary results suggest that this method could potentially be as accurate as the segmented CT method and could be used for quantitative neurologic MR-PET studies.
Ciprian Catana - One of the best experts on this subject based on the ideXlab platform.
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toward implementing an mri based pet attenuation correction method for neurologic studies on the mr pet brain prototype
The Journal of Nuclear Medicine, 2010Co-Authors: Ciprian Catana, Andre J W Van Der Kouwe, Thomas Benner, Christian Michel, Michael Hamm, Matthias Fenchel, Bruce Fischl, Bruce R Rosen, Matthias J Schmand, Gregory A SorensenAbstract:UNLABELLED: Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. METHODS: The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the Radiofrequency Coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. RESULTS: Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm(-1) to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the Radiofrequency Coil attenuation can cause large underestimations (i.e.,
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toward implementing an mri based pet attenuation correction method for neurologic studies on the mr pet brain prototype
The Journal of Nuclear Medicine, 2010Co-Authors: Ciprian Catana, Thomas Benner, Christian Michel, Michael Hamm, Matthias Fenchel, Bruce Fischl, Bruce R Rosen, Matthias J Schmand, Andre J W Van Der Kouwe, Gregory A SorensenAbstract:Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. Methods: The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the Radiofrequency Coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. Results: Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm -1 to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the Radiofrequency Coil attenuation can cause large underestimations (i.e., ≤50%) in the reconstructed images. Furthermore, the Coil location in the PET field of view has to be accurately known. High-quality bone-air segmentation can be performed using the DUTE data. The PET images obtained using the DUTE MRI- and CT-based AC methods compare favorably in most of the brain structures. Conclusion: A DUTE MRI-based AC method considering all these factors was implemented. Preliminary results suggest that this method could potentially be as accurate as the segmented CT method and could be used for quantitative neurologic MR-PET studies.
Matthias Fenchel - One of the best experts on this subject based on the ideXlab platform.
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toward implementing an mri based pet attenuation correction method for neurologic studies on the mr pet brain prototype
The Journal of Nuclear Medicine, 2010Co-Authors: Ciprian Catana, Andre J W Van Der Kouwe, Thomas Benner, Christian Michel, Michael Hamm, Matthias Fenchel, Bruce Fischl, Bruce R Rosen, Matthias J Schmand, Gregory A SorensenAbstract:UNLABELLED: Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. METHODS: The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the Radiofrequency Coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. RESULTS: Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm(-1) to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the Radiofrequency Coil attenuation can cause large underestimations (i.e.,
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toward implementing an mri based pet attenuation correction method for neurologic studies on the mr pet brain prototype
The Journal of Nuclear Medicine, 2010Co-Authors: Ciprian Catana, Thomas Benner, Christian Michel, Michael Hamm, Matthias Fenchel, Bruce Fischl, Bruce R Rosen, Matthias J Schmand, Andre J W Van Der Kouwe, Gregory A SorensenAbstract:Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. Methods: The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the Radiofrequency Coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. Results: Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm -1 to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the Radiofrequency Coil attenuation can cause large underestimations (i.e., ≤50%) in the reconstructed images. Furthermore, the Coil location in the PET field of view has to be accurately known. High-quality bone-air segmentation can be performed using the DUTE data. The PET images obtained using the DUTE MRI- and CT-based AC methods compare favorably in most of the brain structures. Conclusion: A DUTE MRI-based AC method considering all these factors was implemented. Preliminary results suggest that this method could potentially be as accurate as the segmented CT method and could be used for quantitative neurologic MR-PET studies.
Bruce Fischl - One of the best experts on this subject based on the ideXlab platform.
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toward implementing an mri based pet attenuation correction method for neurologic studies on the mr pet brain prototype
The Journal of Nuclear Medicine, 2010Co-Authors: Ciprian Catana, Andre J W Van Der Kouwe, Thomas Benner, Christian Michel, Michael Hamm, Matthias Fenchel, Bruce Fischl, Bruce R Rosen, Matthias J Schmand, Gregory A SorensenAbstract:UNLABELLED: Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. METHODS: The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the Radiofrequency Coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. RESULTS: Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm(-1) to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the Radiofrequency Coil attenuation can cause large underestimations (i.e.,
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toward implementing an mri based pet attenuation correction method for neurologic studies on the mr pet brain prototype
The Journal of Nuclear Medicine, 2010Co-Authors: Ciprian Catana, Thomas Benner, Christian Michel, Michael Hamm, Matthias Fenchel, Bruce Fischl, Bruce R Rosen, Matthias J Schmand, Andre J W Van Der Kouwe, Gregory A SorensenAbstract:Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. Methods: The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the Radiofrequency Coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. Results: Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm -1 to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the Radiofrequency Coil attenuation can cause large underestimations (i.e., ≤50%) in the reconstructed images. Furthermore, the Coil location in the PET field of view has to be accurately known. High-quality bone-air segmentation can be performed using the DUTE data. The PET images obtained using the DUTE MRI- and CT-based AC methods compare favorably in most of the brain structures. Conclusion: A DUTE MRI-based AC method considering all these factors was implemented. Preliminary results suggest that this method could potentially be as accurate as the segmented CT method and could be used for quantitative neurologic MR-PET studies.