The Experts below are selected from a list of 345201 Experts worldwide ranked by ideXlab platform
Anbo Wang - One of the best experts on this subject based on the ideXlab platform.
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frequency estimation based signal Processing Algorithm for white light optical fiber fabry perot interferometers
Applied Optics, 2005Co-Authors: Fabin Shen, Anbo WangAbstract:A novel signal-Processing Algorithm based on frequency estimation of the spectrogram of single-mode optical fiber Fabry–Perot interferometric sensors under white-light illumination is described. The frequency-estimation approach is based on linear regression of the instantaneous phase of an analytical signal, which can be obtained by preProcessing the original spectrogram with a bandpass filter. This method can be used for a relatively large cavity length without the need for spectrogram normalization to the spectrum of the light source and can be extended directly to a multiplexed sensor system. Experimental results show that the method can yield both absolute measurement with high resolution and a large dynamic range. Performance analysis shows that the method is tolerant of background noise and variations of the source spectrum.
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frequency estimation based signal Processing Algorithm for white light optical fiber fabry perot interferometers
Applied Optics, 2005Co-Authors: Fabin Shen, Anbo WangAbstract:A novel signal-Processing Algorithm based on frequency estimation of the spectrogram of single-mode optical fiber Fabry–Perot interferometric sensors under white-light illumination is described. The frequency-estimation approach is based on linear regression of the instantaneous phase of an analytical signal, which can be obtained by preProcessing the original spectrogram with a bandpass filter. This method can be used for a relatively large cavity length without the need for spectrogram normalization to the spectrum of the light source and can be extended directly to a multiplexed sensor system. Experimental results show that the method can yield both absolute measurement with high resolution and a large dynamic range. Performance analysis shows that the method is tolerant of background noise and variations of the source spectrum.
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signal Processing Algorithm for white light optical fiber extrinsic fabry perot interferometric sensors
Optics Letters, 2004Co-Authors: Ming Han, Fabin Shen, Yan Zhang, Gary Pickrell, Anbo WangAbstract:We present a novel signal-Processing Algorithm for single-mode optical fiber extrinsic Fabry–Perot interferometric sensors that can achieve both high-resolution, absolute measurement of the cavity length and a large dynamic measurement range simultaneously. The Algorithm is based on an accurate model of the characteristics of a fiber-optic sensor that takes into account the phase shift that is due to the coupling of light reflected at the second surface to the lead-in fiber end.
Fabin Shen - One of the best experts on this subject based on the ideXlab platform.
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frequency estimation based signal Processing Algorithm for white light optical fiber fabry perot interferometers
Applied Optics, 2005Co-Authors: Fabin Shen, Anbo WangAbstract:A novel signal-Processing Algorithm based on frequency estimation of the spectrogram of single-mode optical fiber Fabry–Perot interferometric sensors under white-light illumination is described. The frequency-estimation approach is based on linear regression of the instantaneous phase of an analytical signal, which can be obtained by preProcessing the original spectrogram with a bandpass filter. This method can be used for a relatively large cavity length without the need for spectrogram normalization to the spectrum of the light source and can be extended directly to a multiplexed sensor system. Experimental results show that the method can yield both absolute measurement with high resolution and a large dynamic range. Performance analysis shows that the method is tolerant of background noise and variations of the source spectrum.
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frequency estimation based signal Processing Algorithm for white light optical fiber fabry perot interferometers
Applied Optics, 2005Co-Authors: Fabin Shen, Anbo WangAbstract:A novel signal-Processing Algorithm based on frequency estimation of the spectrogram of single-mode optical fiber Fabry–Perot interferometric sensors under white-light illumination is described. The frequency-estimation approach is based on linear regression of the instantaneous phase of an analytical signal, which can be obtained by preProcessing the original spectrogram with a bandpass filter. This method can be used for a relatively large cavity length without the need for spectrogram normalization to the spectrum of the light source and can be extended directly to a multiplexed sensor system. Experimental results show that the method can yield both absolute measurement with high resolution and a large dynamic range. Performance analysis shows that the method is tolerant of background noise and variations of the source spectrum.
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signal Processing Algorithm for white light optical fiber extrinsic fabry perot interferometric sensors
Optics Letters, 2004Co-Authors: Ming Han, Fabin Shen, Yan Zhang, Gary Pickrell, Anbo WangAbstract:We present a novel signal-Processing Algorithm for single-mode optical fiber extrinsic Fabry–Perot interferometric sensors that can achieve both high-resolution, absolute measurement of the cavity length and a large dynamic measurement range simultaneously. The Algorithm is based on an accurate model of the characteristics of a fiber-optic sensor that takes into account the phase shift that is due to the coupling of light reflected at the second surface to the lead-in fiber end.
Peter Kellman - One of the best experts on this subject based on the ideXlab platform.
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automatic in line quantitative myocardial perfusion mapping Processing Algorithm and implementation
Magnetic Resonance in Medicine, 2020Co-Authors: Hui Xue, Louise A E Brown, Sonia Niellesvallespin, Sven Plein, Peter KellmanAbstract:PURPOSE Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains a research tool. Building upon the previously described imaging sequence, this study presents Algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization. METHODS Proposed workflow consists of motion correction (MOCO), arterial input function blood detection, intensity to gadolinium concentration conversion, and pixel-wise mapping. A distributed kinetics model, blood-tissue exchange model, is implemented, computing pixel-wise maps of myocardial blood flow (mL/min/g), permeability-surface-area product (mL/min/g), blood volume (mL/g), and interstitial volume (mL/g). RESULTS Thirty healthy subjects (11 men; 26.4 ± 10.4 years) were recruited and underwent adenosine stress perfusion cardiovascular MR. Mean MOCO quality score was 3.6 ± 0.4 for stress and 3.7 ± 0.4 for rest. Myocardial Dice similarity coefficients after MOCO were significantly improved (P < 1e-6), 0.87 ± 0.05 for stress and 0.86 ± 0.06 for rest. Arterial input function peak gadolinium concentration was 4.4 ± 1.3 mmol/L at stress and 5.2 ± 1.5 mmol/L at rest. Mean myocardial blood flow at stress and rest were 2.82 ± 0.47 mL/min/g and 0.68 ± 0.16 mL/min/g, respectively. The permeability-surface-area product was 1.32 ± 0.26 mL/min/g at stress and 1.09 ± 0.21 mL/min/g at rest (P < 1e-3). Blood volume was 12.0 ± 0.8 mL/100 g at stress and 9.7 ± 1.0 mL/100 g at rest (P < 1e-9), indicating good adenosine vasodilation response. Interstitial volume was 20.8 ± 2.5 mL/100 g at stress and 20.3 ± 2.9 mL/100 g at rest (P = 0.50). CONCLUSIONS An inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial evaluation demonstrates this fully automated solution for the respiratory MOCO, arterial input function left ventricle mask detection, and pixel-wise mapping, from free-breathing myocardial perfusion imaging.
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automatic in line quantitative myocardial perfusion mapping Processing Algorithm and implementation
arXiv: Image and Video Processing, 2019Co-Authors: Hui Xue, Louise A E Brown, Sonia Niellesvallespin, Sven Plein, Peter KellmanAbstract:Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains as a research tool. Building upon the previously described imaging sequence, this paper presents Algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization. An inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial evaluation demonstrates the fully automated proposed solution for the respiratory motion correction, AIF LV mask detection and pixel-wise mapping, from free-breathing myocardial perfusion imaging.
Ming Han - One of the best experts on this subject based on the ideXlab platform.
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signal Processing Algorithm for white light optical fiber extrinsic fabry perot interferometric sensors
Optics Letters, 2004Co-Authors: Ming Han, Fabin Shen, Yan Zhang, Gary Pickrell, Anbo WangAbstract:We present a novel signal-Processing Algorithm for single-mode optical fiber extrinsic Fabry–Perot interferometric sensors that can achieve both high-resolution, absolute measurement of the cavity length and a large dynamic measurement range simultaneously. The Algorithm is based on an accurate model of the characteristics of a fiber-optic sensor that takes into account the phase shift that is due to the coupling of light reflected at the second surface to the lead-in fiber end.
Hui Xue - One of the best experts on this subject based on the ideXlab platform.
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automatic in line quantitative myocardial perfusion mapping Processing Algorithm and implementation
Magnetic Resonance in Medicine, 2020Co-Authors: Hui Xue, Louise A E Brown, Sonia Niellesvallespin, Sven Plein, Peter KellmanAbstract:PURPOSE Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains a research tool. Building upon the previously described imaging sequence, this study presents Algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization. METHODS Proposed workflow consists of motion correction (MOCO), arterial input function blood detection, intensity to gadolinium concentration conversion, and pixel-wise mapping. A distributed kinetics model, blood-tissue exchange model, is implemented, computing pixel-wise maps of myocardial blood flow (mL/min/g), permeability-surface-area product (mL/min/g), blood volume (mL/g), and interstitial volume (mL/g). RESULTS Thirty healthy subjects (11 men; 26.4 ± 10.4 years) were recruited and underwent adenosine stress perfusion cardiovascular MR. Mean MOCO quality score was 3.6 ± 0.4 for stress and 3.7 ± 0.4 for rest. Myocardial Dice similarity coefficients after MOCO were significantly improved (P < 1e-6), 0.87 ± 0.05 for stress and 0.86 ± 0.06 for rest. Arterial input function peak gadolinium concentration was 4.4 ± 1.3 mmol/L at stress and 5.2 ± 1.5 mmol/L at rest. Mean myocardial blood flow at stress and rest were 2.82 ± 0.47 mL/min/g and 0.68 ± 0.16 mL/min/g, respectively. The permeability-surface-area product was 1.32 ± 0.26 mL/min/g at stress and 1.09 ± 0.21 mL/min/g at rest (P < 1e-3). Blood volume was 12.0 ± 0.8 mL/100 g at stress and 9.7 ± 1.0 mL/100 g at rest (P < 1e-9), indicating good adenosine vasodilation response. Interstitial volume was 20.8 ± 2.5 mL/100 g at stress and 20.3 ± 2.9 mL/100 g at rest (P = 0.50). CONCLUSIONS An inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial evaluation demonstrates this fully automated solution for the respiratory MOCO, arterial input function left ventricle mask detection, and pixel-wise mapping, from free-breathing myocardial perfusion imaging.
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automatic in line quantitative myocardial perfusion mapping Processing Algorithm and implementation
arXiv: Image and Video Processing, 2019Co-Authors: Hui Xue, Louise A E Brown, Sonia Niellesvallespin, Sven Plein, Peter KellmanAbstract:Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains as a research tool. Building upon the previously described imaging sequence, this paper presents Algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization. An inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial evaluation demonstrates the fully automated proposed solution for the respiratory motion correction, AIF LV mask detection and pixel-wise mapping, from free-breathing myocardial perfusion imaging.
