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Ehsan Samei - One of the best experts on this subject based on the ideXlab platform.
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assessment of volumetric noise and Resolution Performance for linear and nonlinear ct reconstruction methods
Medical Physics, 2014Co-Authors: Baiyu Chen, O Christianson, Joshua M. Wilson, Ehsan SameiAbstract:Purpose: For nonlinear iterative image reconstructions (IR), the computed tomography (CT) noise and Resolution properties can depend on the specific imaging conditions, such as lesion contrast and image noise level. Therefore, it is imperative to develop a reliable method to measure the noise and Resolution properties under clinically relevant conditions. This study aimed to develop a robust methodology to measure the three-dimensional CT noise and Resolution properties under such conditions and to provide guidelines to achieve desirable levels of accuracy and precision. Methods: The methodology was developed based on a previously reported CT image quality phantom. In this methodology, CT noise properties are measured in the uniform region of the phantom in terms of a task-based 3D noise-power spectrum (NPS{sub task}). The in-plane Resolution properties are measured in terms of the task transfer function (TTF) by applying a radial edge technique to the rod inserts in the phantom. The z-direction Resolution properties are measured from a supplemental phantom, also in terms of the TTF. To account for the possible nonlinearity of IR, the NPS{sub task} is measured with respect to the noise magnitude, and the TTF with respect to noise magnitude and edge contrast. To determine the accuracy and precisionmore » of the methodology, images of known noise and Resolution properties were simulated. The NPS{sub task} and TTF were measured on the simulated images and compared to the truth, with criteria established to achieve NPS{sub task} and TTF measurements with <10% error. To demonstrate the utility of this methodology, measurements were performed on a commercial CT system using five dose levels, two slice thicknesses, and three reconstruction algorithms (filtered backprojection, FBP; iterative reconstruction in imaging space, IRIS; and sinogram affirmed iterative reconstruction with strengths of 5, SAFIRE5). Results: To achieve NPS{sub task} measurements with <10% error, the number of regions of interest needed to be greater than 65. To achieve TTF measurements with <10% error, the contrast-to-noise ratio of the edge needed to be ≥15, achievable by averaging multiple slices across the same edge. The NPS{sub task} measured on a commercial CT system showed IR's reduced noise (IRIS, 30% and SAFIRE5, 55%) and “waxier” texture (peak frequencies: FBP, 0.25 mm{sup −1}; IRIS, 0.23 mm{sup −1}; and SAFIRE5, 0.16 mm{sup −1}). The TTF measured within the axial plane showed improved in-plane Resolution with SAFIRE5 at the TTF 50% frequency, f{sub 50} (FBP, 0.36–0.41 mm{sup −1}; SAFIRE5, 0.37–0.46 mm{sup −1}). The TTF measured along the axial direction showed improved z-direction Resolution with thinner slice thickness (f{sub 50}: 0.6 mm, 0.35–0.79 mm{sup −1}; 1.5 mm, 0.22–0.3 mm{sup −1}) and with SAFIRE5 (f{sub 50}: FBP, 0.35–0.52 mm{sup −1}; SAFIRE5, 0.42–0.79 mm{sup −1}). Both in-plane and z-direction Resolution of SAFIRE5 showed strong dependency on contrast, reflecting SAFIRE5's nonlinearity. Conclusions: A methodology was developed to measure three-dimensional CT noise and Resolution properties for iterative reconstruction, especially at challenging measurement conditions with low contrast and high image noise. The methodology also demonstrated its utility for evaluating commercial CT systems.« less
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Assessment of volumetric noise and Resolution Performance for linear and nonlinear CT reconstruction methods.
Medical Physics, 2014Co-Authors: Baiyu Chen, O Christianson, Joshua M. Wilson, Ehsan SameiAbstract:Purpose: For nonlinear iterative image reconstructions (IR), the computed tomography (CT) noise and Resolution properties can depend on the specific imaging conditions, such as lesion contrast and image noise level. Therefore, it is imperative to develop a reliable method to measure the noise and Resolution properties under clinically relevant conditions. This study aimed to develop a robust methodology to measure the three-dimensional CT noise and Resolution properties under such conditions and to provide guidelines to achieve desirable levels of accuracy and precision. Methods: The methodology was developed based on a previously reported CT image quality phantom. In this methodology, CT noise properties are measured in the uniform region of the phantom in terms of a task-based 3D noise-power spectrum (NPS{sub task}). The in-plane Resolution properties are measured in terms of the task transfer function (TTF) by applying a radial edge technique to the rod inserts in the phantom. The z-direction Resolution properties are measured from a supplemental phantom, also in terms of the TTF. To account for the possible nonlinearity of IR, the NPS{sub task} is measured with respect to the noise magnitude, and the TTF with respect to noise magnitude and edge contrast. To determine the accuracy and precisionmore » of the methodology, images of known noise and Resolution properties were simulated. The NPS{sub task} and TTF were measured on the simulated images and compared to the truth, with criteria established to achieve NPS{sub task} and TTF measurements with
Viktor Sucic - One of the best experts on this subject based on the ideXlab platform.
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Resolution Performance assessment for comparing and selecting quadratic tfds
2015Co-Authors: B. Boashash, Viktor SucicAbstract:The work presents an objective criteria for Resolution Performance assessment in comparing and selecting Quadratic TFDs.
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Resolution Performance assessment for quadratic tfds
TIme-Frequency Signal Analysis and Processing: A Comprehensive Reference, 2003Co-Authors: B. Boashash, Viktor SucicAbstract:Quadratic time-frequency distributions (TFDs) are effective tools for extracting information from a non-stationary signal, such as the number of components, their durations and bandwidths, components’ relative amplitudes and instantaneous frequency (IF) laws (see Chapters 1 and 2). The Performance of TFDs depends on the type of signal (see Chapter 3) [1,2]. For example, in the case of a monocomponent linear FM signal, the Wigner-Ville distribution is known to be optimal in the sense that it achieves the best energy concentration around the signal IF law (see Article 2.1 for more details) [1]. In applications involving multicomponent signals, choosing the right TFD to analyze the signals is an immediate critical task for the signal analyst. How best to make this assessment, using current knowledge, is the subject of this article. Let us, for example, consider a multicomponent whale signal, represented in the time-frequency domain using the Wigner-Ville distribution, the spectrogram, the Choi-Williams distribution, the Born-Jordan distribution, the Zhao-Atlas-Marks (ZAM) distribution, and the recently introduced B-distribution [3] (see Fig. 7.4.1). To determine which of the TFDs in Fig. 7.4.1 “best” represents this whale signal (i.e. which one gives the best components’ energy concentration and best interference terms suppression, and allows the best estimation of the components’ IF laws) one could visually compare the six plots and choose the most appealing. The spectrogram and the B-distribution, being almost free from the cross-terms, seem to perform best. The Performance comparison based on the visual inspection of the plots becomes more difficult and unreliable, however, when the signal components are closelyspaced in the time-frequency plane. To objectively compare the plots in Fig. 7.4.1 requires to use a quantitative Performance measure for TFDs. There have been several attempts to define objective measures of “complexity” for TFDs (see Section 7.3.1). One of these measures, the Renyi entropy given in [4], has been used by several authors in preference to e.g. the bandwidth–duration product given in [1]. The Performance measure described in this article, unlike the Renyi entropy, is a local measure of the TFD Resolution Performance, and is thus more suited to the selection problem illustrated by Fig. 7.4.1. This measure takes into account the characteristics of TFDs that influence their Resolution, such as energy concentration, components separation, and interference terms minimization. Methodologies for choosing a TFD which best suits a given signal can then be developed by optimizing the Resolution Performance of considered TFDs and modifying their parameters to better match application-specific requirements.
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A Resolution Performance measure for quadratic time-frequency distributions
Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing (Cat. No.00TH8496), 2000Co-Authors: B. Boashash, Viktor SucicAbstract:This paper presents two novel results which are significant for the application of time-frequency signal analysis techniques to real life signals. First, we introduce a measure for comparing the Resolution Performance of TFDs in separating closely spaced components in the time-frequency domain. The measure takes into account key attributes of TFDs such as main-lobes, side-lobes, and cross-terms. The introduction of this measure is an improvement of current techniques which rely on visual inspection of plots. The second result consists in proposing a methodology for designing high Resolution quadratic TFDs for the time-frequency analysis of multicomponent signals when components are close to each other. A recently introduced TFD, the B-distribution, and its modified version are defined using this methodology. Finally, the Performance comparison of quadratic TFDs using the proposed Resolution measure shows that the B-distribution outperforms existing quadratic TFDs in resolving closely spaced components in the time-frequency domain.
Xiaoqiang Luo - One of the best experts on this subject based on the ideXlab platform.
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on coreference Resolution Performance metrics
Empirical Methods in Natural Language Processing, 2005Co-Authors: Xiaoqiang LuoAbstract:The paper proposes a Constrained Entity-Alignment F-Measure (CEAF) for evaluating coreference Resolution. The metric is computed by aligning reference and system entities (or coreference chains) with the constraint that a system (reference) entity is aligned with at most one reference (system) entity. We show that the best alignment is a maximum bipartite matching problem which can be solved by the Kuhn-Munkres algorithm. Comparative experiments are conducted to show that the widely-known MUC F-measure has serious flaws in evaluating a coreference system. The proposed metric is also compared with the ACE-Value, the official evaluation metric in the Automatic Content Extraction (ACE) task, and we conclude that the proposed metric possesses some properties such as symmetry and better interpretability missing in the ACE-Value.
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HLT/EMNLP - On Coreference Resolution Performance Metrics
Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05, 2005Co-Authors: Xiaoqiang LuoAbstract:The paper proposes a Constrained Entity-Alignment F-Measure (CEAF) for evaluating coreference Resolution. The metric is computed by aligning reference and system entities (or coreference chains) with the constraint that a system (reference) entity is aligned with at most one reference (system) entity. We show that the best alignment is a maximum bipartite matching problem which can be solved by the Kuhn-Munkres algorithm. Comparative experiments are conducted to show that the widely-known MUC F-measure has serious flaws in evaluating a coreference system. The proposed metric is also compared with the ACE-Value, the official evaluation metric in the Automatic Content Extraction (ACE) task, and we conclude that the proposed metric possesses some properties such as symmetry and better interpretability missing in the ACE-Value.
Baiyu Chen - One of the best experts on this subject based on the ideXlab platform.
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assessment of volumetric noise and Resolution Performance for linear and nonlinear ct reconstruction methods
Medical Physics, 2014Co-Authors: Baiyu Chen, O Christianson, Joshua M. Wilson, Ehsan SameiAbstract:Purpose: For nonlinear iterative image reconstructions (IR), the computed tomography (CT) noise and Resolution properties can depend on the specific imaging conditions, such as lesion contrast and image noise level. Therefore, it is imperative to develop a reliable method to measure the noise and Resolution properties under clinically relevant conditions. This study aimed to develop a robust methodology to measure the three-dimensional CT noise and Resolution properties under such conditions and to provide guidelines to achieve desirable levels of accuracy and precision. Methods: The methodology was developed based on a previously reported CT image quality phantom. In this methodology, CT noise properties are measured in the uniform region of the phantom in terms of a task-based 3D noise-power spectrum (NPS{sub task}). The in-plane Resolution properties are measured in terms of the task transfer function (TTF) by applying a radial edge technique to the rod inserts in the phantom. The z-direction Resolution properties are measured from a supplemental phantom, also in terms of the TTF. To account for the possible nonlinearity of IR, the NPS{sub task} is measured with respect to the noise magnitude, and the TTF with respect to noise magnitude and edge contrast. To determine the accuracy and precisionmore » of the methodology, images of known noise and Resolution properties were simulated. The NPS{sub task} and TTF were measured on the simulated images and compared to the truth, with criteria established to achieve NPS{sub task} and TTF measurements with <10% error. To demonstrate the utility of this methodology, measurements were performed on a commercial CT system using five dose levels, two slice thicknesses, and three reconstruction algorithms (filtered backprojection, FBP; iterative reconstruction in imaging space, IRIS; and sinogram affirmed iterative reconstruction with strengths of 5, SAFIRE5). Results: To achieve NPS{sub task} measurements with <10% error, the number of regions of interest needed to be greater than 65. To achieve TTF measurements with <10% error, the contrast-to-noise ratio of the edge needed to be ≥15, achievable by averaging multiple slices across the same edge. The NPS{sub task} measured on a commercial CT system showed IR's reduced noise (IRIS, 30% and SAFIRE5, 55%) and “waxier” texture (peak frequencies: FBP, 0.25 mm{sup −1}; IRIS, 0.23 mm{sup −1}; and SAFIRE5, 0.16 mm{sup −1}). The TTF measured within the axial plane showed improved in-plane Resolution with SAFIRE5 at the TTF 50% frequency, f{sub 50} (FBP, 0.36–0.41 mm{sup −1}; SAFIRE5, 0.37–0.46 mm{sup −1}). The TTF measured along the axial direction showed improved z-direction Resolution with thinner slice thickness (f{sub 50}: 0.6 mm, 0.35–0.79 mm{sup −1}; 1.5 mm, 0.22–0.3 mm{sup −1}) and with SAFIRE5 (f{sub 50}: FBP, 0.35–0.52 mm{sup −1}; SAFIRE5, 0.42–0.79 mm{sup −1}). Both in-plane and z-direction Resolution of SAFIRE5 showed strong dependency on contrast, reflecting SAFIRE5's nonlinearity. Conclusions: A methodology was developed to measure three-dimensional CT noise and Resolution properties for iterative reconstruction, especially at challenging measurement conditions with low contrast and high image noise. The methodology also demonstrated its utility for evaluating commercial CT systems.« less
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Assessment of volumetric noise and Resolution Performance for linear and nonlinear CT reconstruction methods.
Medical Physics, 2014Co-Authors: Baiyu Chen, O Christianson, Joshua M. Wilson, Ehsan SameiAbstract:Purpose: For nonlinear iterative image reconstructions (IR), the computed tomography (CT) noise and Resolution properties can depend on the specific imaging conditions, such as lesion contrast and image noise level. Therefore, it is imperative to develop a reliable method to measure the noise and Resolution properties under clinically relevant conditions. This study aimed to develop a robust methodology to measure the three-dimensional CT noise and Resolution properties under such conditions and to provide guidelines to achieve desirable levels of accuracy and precision. Methods: The methodology was developed based on a previously reported CT image quality phantom. In this methodology, CT noise properties are measured in the uniform region of the phantom in terms of a task-based 3D noise-power spectrum (NPS{sub task}). The in-plane Resolution properties are measured in terms of the task transfer function (TTF) by applying a radial edge technique to the rod inserts in the phantom. The z-direction Resolution properties are measured from a supplemental phantom, also in terms of the TTF. To account for the possible nonlinearity of IR, the NPS{sub task} is measured with respect to the noise magnitude, and the TTF with respect to noise magnitude and edge contrast. To determine the accuracy and precisionmore » of the methodology, images of known noise and Resolution properties were simulated. The NPS{sub task} and TTF were measured on the simulated images and compared to the truth, with criteria established to achieve NPS{sub task} and TTF measurements with
Thomas Walz - One of the best experts on this subject based on the ideXlab platform.
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evaluation of super Resolution Performance of the k2 electron counting camera using 2d crystals of aquaporin 0
Journal of Structural Biology, 2015Co-Authors: Polin Chiu, Brian C Beckett, Axel F Brilot, Nikolaus Grigorieff, David A Agard, Yifan Cheng, Thomas WalzAbstract:The K2 Summit camera was initially the only commercially available direct electron detection camera that was optimized for high-speed counting of primary electrons and was also the only one that implemented centroiding so that the Resolution of the camera can be extended beyond the Nyquist limit set by the physical pixel size. In this study, we used well-characterized two-dimensional crystals of the membrane protein aquaporin-0 to characterize the Performance of the camera below and beyond the physical Nyquist limit and to measure the influence of electron dose rate on image amplitudes and phases.
