Pub Date : 2020-01-07DOI: 10.1103/physrevapplied.14.011002
M. Limes, E. Foley, T. Kornack, S. Caliga, S. McBride, A. Braun, W. Lee, V. Lucivero, M. Romalis
We present a method of optical magnetometry with parts-per-billion resolution that is able to detect biomagnetic signals generated from the human brain and heart in Earth's ambient environment. Our magnetically silent sensors measure the total magnetic field by detecting the free-precession frequency of highly spin-polarized alkali metal vapor. A first-order gradiometer is formed from two magnetometers that are separated by a 3 cm baseline. Our gradiometer operates from a laptop consuming 5 W over a USB port, enabled by state-of-the-art micro-fabricated alkali vapor cells, advanced thermal insulation, custom electronics, and laser packages within the sensor head. The gradiometer obtains a sensitivity of 16 fT/cm/Hz$^{1/2}$ outdoors, which we use to detect neuronal electrical currents and magnetic cardiography signals. Recording of neuronal magnetic fields is one of a few available methods for non-invasive functional brain imaging that usually requires extensive magnetic shielding and other infractructure. This work demonstrates the possibility of a dense array of portable biomagnetic sensors that are deployable in a variety of natural environments.
{"title":"Portable Magnetometry for Detection of Biomagnetism in Ambient Environments","authors":"M. Limes, E. Foley, T. Kornack, S. Caliga, S. McBride, A. Braun, W. Lee, V. Lucivero, M. Romalis","doi":"10.1103/physrevapplied.14.011002","DOIUrl":"https://doi.org/10.1103/physrevapplied.14.011002","url":null,"abstract":"We present a method of optical magnetometry with parts-per-billion resolution that is able to detect biomagnetic signals generated from the human brain and heart in Earth's ambient environment. Our magnetically silent sensors measure the total magnetic field by detecting the free-precession frequency of highly spin-polarized alkali metal vapor. A first-order gradiometer is formed from two magnetometers that are separated by a 3 cm baseline. Our gradiometer operates from a laptop consuming 5 W over a USB port, enabled by state-of-the-art micro-fabricated alkali vapor cells, advanced thermal insulation, custom electronics, and laser packages within the sensor head. The gradiometer obtains a sensitivity of 16 fT/cm/Hz$^{1/2}$ outdoors, which we use to detect neuronal electrical currents and magnetic cardiography signals. Recording of neuronal magnetic fields is one of a few available methods for non-invasive functional brain imaging that usually requires extensive magnetic shielding and other infractructure. This work demonstrates the possibility of a dense array of portable biomagnetic sensors that are deployable in a variety of natural environments.","PeriodicalId":8462,"journal":{"name":"arXiv: Medical Physics","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77582676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-21DOI: 10.1016/j.jmps.2020.104014
Mohammad Masiur Rahaman, Wenqiang Fang, A. Fawzi, Yang Wan, H. Kesari
{"title":"An accelerometer-only algorithm for determining the acceleration field of a rigid body, with application in studying the mechanics of mild traumatic brain injury","authors":"Mohammad Masiur Rahaman, Wenqiang Fang, A. Fawzi, Yang Wan, H. Kesari","doi":"10.1016/j.jmps.2020.104014","DOIUrl":"https://doi.org/10.1016/j.jmps.2020.104014","url":null,"abstract":"","PeriodicalId":8462,"journal":{"name":"arXiv: Medical Physics","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85943967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yixun Xing, D. Nguyen, W. Lu, Ming Yang, Steve B. Jiang
Purpose: Various dose calculation algorithms are available for radiation therapy for cancer patients. However, these algorithms are faced with the tradeoff between efficiency and accuracy. The fast algorithms are generally less accurate, while the accurate dose engines are often time consuming. In this work, we try to resolve this dilemma by exploring deep learning (DL) for dose calculation. Methods: We developed a new radiotherapy dose calculation engine based on a modified Hierarchically Densely Connected U-net (HD U-net) model and tested its feasibility with prostate intensity-modulated radiation therapy (IMRT) cases. Mapping from an IMRT fluence map domain to a 3D dose domain requires a deep neural network of complicated architecture and a huge training dataset. To solve this problem, we first project the fluence maps to the dose domain using a modified ray-tracing algorithm, and then we use the HD U-net to map the ray-tracing dose distribution into an accurate dose distribution calculated using a collapsed cone convolution/superposition (CS) algorithm. Results: It takes about one second to compute a 3D dose distribution for a typical 7-field prostate IMRT plan, which can be further reduced to achieve real-time dose calculation by optimizing the network. For all eight testing patients, evaluation with Gamma Index and various clinical goals for IMRT optimization shows that the DL dose distributions are clinically identical to the CS dose distributions. Conclusions: We have shown the feasibility of using DL for calculating radiotherapy dose distribution with high accuracy and efficiency.
{"title":"A Feasibility Study on Deep Learning-Based Radiotherapy Dose Calculation","authors":"Yixun Xing, D. Nguyen, W. Lu, Ming Yang, Steve B. Jiang","doi":"10.1002/MP.13953","DOIUrl":"https://doi.org/10.1002/MP.13953","url":null,"abstract":"Purpose: Various dose calculation algorithms are available for radiation therapy for cancer patients. However, these algorithms are faced with the tradeoff between efficiency and accuracy. The fast algorithms are generally less accurate, while the accurate dose engines are often time consuming. In this work, we try to resolve this dilemma by exploring deep learning (DL) for dose calculation. Methods: We developed a new radiotherapy dose calculation engine based on a modified Hierarchically Densely Connected U-net (HD U-net) model and tested its feasibility with prostate intensity-modulated radiation therapy (IMRT) cases. Mapping from an IMRT fluence map domain to a 3D dose domain requires a deep neural network of complicated architecture and a huge training dataset. To solve this problem, we first project the fluence maps to the dose domain using a modified ray-tracing algorithm, and then we use the HD U-net to map the ray-tracing dose distribution into an accurate dose distribution calculated using a collapsed cone convolution/superposition (CS) algorithm. Results: It takes about one second to compute a 3D dose distribution for a typical 7-field prostate IMRT plan, which can be further reduced to achieve real-time dose calculation by optimizing the network. For all eight testing patients, evaluation with Gamma Index and various clinical goals for IMRT optimization shows that the DL dose distributions are clinically identical to the CS dose distributions. Conclusions: We have shown the feasibility of using DL for calculating radiotherapy dose distribution with high accuracy and efficiency.","PeriodicalId":8462,"journal":{"name":"arXiv: Medical Physics","volume":"62 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85784281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-31DOI: 10.1103/PHYSREVAPPLIED.13.054023
K. Pavlov, H. Li, D. Paganin, S. Berujon, H'elene Roug'e-Labriet, E. Brun
We develop a means for speckle-based phase imaging of the projected thickness of a single-material object, under the assumption of illumination by spatially random time-independent x-ray speckles. These speckles are generated by passing x rays through a suitable spatially random mask. The method makes use of a single image obtained in the presence of the object, which serves to deform the illuminating speckle field relative to a reference speckle field (which only needs to be measured once) obtained in the presence of the mask and the absence of the object. The method implicitly rather than explicitly tracks speckles, and utilizes the transport-of-intensity equation to give a closed-form solution to the inverse problem of determining the complex transmission function of the object. Implementation using x-ray synchrotron data shows the method to be robust and efficient with respect to noise. Applications include x-ray phase--amplitude radiography and tomography, as well as time-dependent imaging of dynamic and radiation-sensitive samples using low-flux sources.
{"title":"Single-Shot X-Ray Speckle-Based Imaging of a Single-Material Object","authors":"K. Pavlov, H. Li, D. Paganin, S. Berujon, H'elene Roug'e-Labriet, E. Brun","doi":"10.1103/PHYSREVAPPLIED.13.054023","DOIUrl":"https://doi.org/10.1103/PHYSREVAPPLIED.13.054023","url":null,"abstract":"We develop a means for speckle-based phase imaging of the projected thickness of a single-material object, under the assumption of illumination by spatially random time-independent x-ray speckles. These speckles are generated by passing x rays through a suitable spatially random mask. The method makes use of a single image obtained in the presence of the object, which serves to deform the illuminating speckle field relative to a reference speckle field (which only needs to be measured once) obtained in the presence of the mask and the absence of the object. The method implicitly rather than explicitly tracks speckles, and utilizes the transport-of-intensity equation to give a closed-form solution to the inverse problem of determining the complex transmission function of the object. Implementation using x-ray synchrotron data shows the method to be robust and efficient with respect to noise. Applications include x-ray phase--amplitude radiography and tomography, as well as time-dependent imaging of dynamic and radiation-sensitive samples using low-flux sources.","PeriodicalId":8462,"journal":{"name":"arXiv: Medical Physics","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82084148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-24DOI: 10.1007/978-3-658-25326-4_53
B. Mittmann, A. Seitel, L. Maier-Hein, A. Franz
{"title":"Navigated interventions in the head and neck area: standardized assessment of a new handy field generator.","authors":"B. Mittmann, A. Seitel, L. Maier-Hein, A. Franz","doi":"10.1007/978-3-658-25326-4_53","DOIUrl":"https://doi.org/10.1007/978-3-658-25326-4_53","url":null,"abstract":"","PeriodicalId":8462,"journal":{"name":"arXiv: Medical Physics","volume":"114 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76823747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose: Parallel imaging methods in MRI have resulted in faster acquisition times and improved noise performance. ESPIRiT is one such technique that estimates coil sensitivity maps from the auto-calibration region using an eigenvalue-based method. This method requires choosing several parameters for the the map estimation. Even though ESPIRiT is fairly robust to these parameter choices, occasionally, poor selection can result in reduced performance. The purpose of this work is to automatically select parameters in ESPIRiT for more robust and consistent performance across a variety of exams. Theory and Methods: Stein's unbiased risk estimate (SURE) is a method of calculating an unbiased estimate of the mean squared error of an estimator under certain assumptions. We show that this can be used to estimate the performance of ESPIRiT. We derive and demonstrate the use of SURE to optimize ESPIRiT parameter selection. Results: Simulations show SURE to be an accurate estimator of the mean squared error. SURE is then used to optimize ESPIRiT parameters to yield maps that are optimal in a denoising/data-consistency sense. This improves g-factor performance without causing undesirable attenuation. In-vivo experiments verify the reliability of this method. Conclusion: Simulation experiments demonstrate that SURE is an accurate estimate of expected mean squared error. Using SURE to determine ESPIRiT parameters allows for automatic parameter this http URL-vivo results are consistent with simulation and theoretical results.
{"title":"SURE-based Automatic Parameter Selection For ESPIRiT Calibration","authors":"S. Iyer, Frank Ong, M. Doneva, M. Lustig","doi":"10.1002/MRM.2838","DOIUrl":"https://doi.org/10.1002/MRM.2838","url":null,"abstract":"Purpose: Parallel imaging methods in MRI have resulted in faster acquisition times and improved noise performance. ESPIRiT is one such technique that estimates coil sensitivity maps from the auto-calibration region using an eigenvalue-based method. This method requires choosing several parameters for the the map estimation. Even though ESPIRiT is fairly robust to these parameter choices, occasionally, poor selection can result in reduced performance. The purpose of this work is to automatically select parameters in ESPIRiT for more robust and consistent performance across a variety of exams. \u0000Theory and Methods: Stein's unbiased risk estimate (SURE) is a method of calculating an unbiased estimate of the mean squared error of an estimator under certain assumptions. We show that this can be used to estimate the performance of ESPIRiT. We derive and demonstrate the use of SURE to optimize ESPIRiT parameter selection. \u0000Results: Simulations show SURE to be an accurate estimator of the mean squared error. SURE is then used to optimize ESPIRiT parameters to yield maps that are optimal in a denoising/data-consistency sense. This improves g-factor performance without causing undesirable attenuation. In-vivo experiments verify the reliability of this method. \u0000Conclusion: Simulation experiments demonstrate that SURE is an accurate estimate of expected mean squared error. Using SURE to determine ESPIRiT parameters allows for automatic parameter this http URL-vivo results are consistent with simulation and theoretical results.","PeriodicalId":8462,"journal":{"name":"arXiv: Medical Physics","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84987972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-02DOI: 10.5121/ijfcst.2018.8201
Maxwell Scale Uwadia Osagie, O. Enagbonma, Amanda Iriagbonse Inyang
This research paper examined and re-evaluates the technological innovation, theory, structural dynamics and evolution of Pill Camera (Capsule Endoscopy) technology in redirecting the response manner of small bowel (intestine) examination in human.
{"title":"Structural Dynamics and Evolution of Capsule Endoscopy (Pill Camera) Technology in Gastroenterologist Assertion","authors":"Maxwell Scale Uwadia Osagie, O. Enagbonma, Amanda Iriagbonse Inyang","doi":"10.5121/ijfcst.2018.8201","DOIUrl":"https://doi.org/10.5121/ijfcst.2018.8201","url":null,"abstract":"This research paper examined and re-evaluates the technological innovation, theory, structural dynamics and evolution of Pill Camera (Capsule Endoscopy) technology in redirecting the response manner of small bowel (intestine) examination in human.","PeriodicalId":8462,"journal":{"name":"arXiv: Medical Physics","volume":"148 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79840107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Xiao, V. Mazlin, K. Grieve, J. Sahel, M. Fink, A. Boccara
As the lateral resolution of FFOCT with spatially incoherent illumination has been shown to be insensitive to aberrations, we demonstrate high resolution en face full-field OCT (FFOCT) retinal imaging without wavefront correction in the human eye in vivo for the first time. A combination of FFOCT with spectral-domain OCT (SDOCT) is applied for real-time matching of the optical path lengths (OPL) of FFOCT. Through the real-time cross-sectional SDOCT images, the OPL of the FFOCT reference arm is matched with different retinal layers in the FFOCT sample arm. Thus, diffraction limited FFOCT images of multiple retinal layers are acquired at both the near periphery and the fovea. The en face FFOCT retinal images reveal information about various structures such as the nerve fiber orientation, the blood vessel distribution, and the photoreceptor mosaic.
{"title":"In vivo high resolution human retinal imaging with wavefront correctionless full-field OCT","authors":"P. Xiao, V. Mazlin, K. Grieve, J. Sahel, M. Fink, A. Boccara","doi":"10.1364/OPTICA.5.000409","DOIUrl":"https://doi.org/10.1364/OPTICA.5.000409","url":null,"abstract":"As the lateral resolution of FFOCT with spatially incoherent illumination has been shown to be insensitive to aberrations, we demonstrate high resolution en face full-field OCT (FFOCT) retinal imaging without wavefront correction in the human eye in vivo for the first time. A combination of FFOCT with spectral-domain OCT (SDOCT) is applied for real-time matching of the optical path lengths (OPL) of FFOCT. Through the real-time cross-sectional SDOCT images, the OPL of the FFOCT reference arm is matched with different retinal layers in the FFOCT sample arm. Thus, diffraction limited FFOCT images of multiple retinal layers are acquired at both the near periphery and the fovea. The en face FFOCT retinal images reveal information about various structures such as the nerve fiber orientation, the blood vessel distribution, and the photoreceptor mosaic.","PeriodicalId":8462,"journal":{"name":"arXiv: Medical Physics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75696427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Maeda, A. Maxwell, W. Kreider, T. Colonius, M. Bailey
We conduct experiments and numerical simulations of the dynamics of bubble clouds nucleated on the surface of an epoxy cylindrical stone model during burst wave lithotripsy (BWL). In the experiment, the bubble clouds are visualized and bubble-scattered acoustics are measured. In the numerical simulation, we combine methods for modeling compressible multicomponent flows to capture complex interactions among cavitation bubbles, the stone, and the burst wave. Quantitative agreement is confirmed between results of the experiment and the simulation. We observe and quantify a significant shielding of incident wave energy by the bubble clouds. The magnitude of shielding reaches up to 80% of the total acoustic energy of the incoming burst wave, suggesting a potential loss of efficacy of stone comminution. We further discovered a strong linear correlation between the magnitude of the energy shielding and the amplitude of the bubble-scattered acoustics, independent of the initial size and the void fraction of the bubble cloud within a range addressed in the simulation. This correlation could provide for real-time monitoring of cavitation activity in BWL.
{"title":"Investigation of the energy shielding of kidney stones by cavitation bubble clouds during burst wave lithotripsy","authors":"K. Maeda, A. Maxwell, W. Kreider, T. Colonius, M. Bailey","doi":"10.1115/1.861851_ch119","DOIUrl":"https://doi.org/10.1115/1.861851_ch119","url":null,"abstract":"We conduct experiments and numerical simulations of the dynamics of bubble clouds nucleated on the surface of an epoxy cylindrical stone model during burst wave lithotripsy (BWL). In the experiment, the bubble clouds are visualized and bubble-scattered acoustics are measured. In the numerical simulation, we combine methods for modeling compressible multicomponent flows to capture complex interactions among cavitation bubbles, the stone, and the burst wave. Quantitative agreement is confirmed between results of the experiment and the simulation. We observe and quantify a significant shielding of incident wave energy by the bubble clouds. The magnitude of shielding reaches up to 80% of the total acoustic energy of the incoming burst wave, suggesting a potential loss of efficacy of stone comminution. We further discovered a strong linear correlation between the magnitude of the energy shielding and the amplitude of the bubble-scattered acoustics, independent of the initial size and the void fraction of the bubble cloud within a range addressed in the simulation. This correlation could provide for real-time monitoring of cavitation activity in BWL.","PeriodicalId":8462,"journal":{"name":"arXiv: Medical Physics","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74305090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1016/j.irbm.2017.12.001
C. Papadacci, T. Mirault, B. Dizier, M. Tanter, E. Messas, M. Pernot
{"title":"Non-invasive Evaluation of Aortic Stiffness Dependence with Aortic Blood Pressure and Internal Radius by Shear Wave Elastography and Ultrafast Imaging","authors":"C. Papadacci, T. Mirault, B. Dizier, M. Tanter, E. Messas, M. Pernot","doi":"10.1016/j.irbm.2017.12.001","DOIUrl":"https://doi.org/10.1016/j.irbm.2017.12.001","url":null,"abstract":"","PeriodicalId":8462,"journal":{"name":"arXiv: Medical Physics","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89710954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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