DOCSLIB.ORG

Acknowledgements

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Acknowledgements Amir Pourmorteza Fully 3D Recon 2015 [email protected] May 31 -June 4 Fully 3D Conference 2015 Reconstruction of Difference using Prior Images and a Penalized-Likelihood Framework Amir Pourmorteza, Hao Dang, Jeffrey Siewerdsen, J. Webster Stayman Department of Biomedical Engineering, Johns Hopkins University Johns Hopkins University Schools of Medicine and Engineering Acknowledgements AIAI Laboratory Advanced Imaging Algorithms and Instrumentation Lab aiai.jhu.edu [email protected] I-STAR Laboratory Imaging for Surgery, Therapy, and Radiology istar.jhu.edu [email protected] Faculty and Scientists Clinical Partners Students Industry Partners Tharindu De Silva Junghoon Lee Qian Cao Lyn Hibbard Grace Gang John Wong Hao Dang Xiao Han Aswin Mathews Sarah Ouadah Markus Eriksson Amir Pourmorteza Sureerat Reaungamornrat Himu Shukla Jeffrey Siewerdsen Steven Tilley II Alejandro Sisniega Ali Uneri J. Webster Stayman Jennifer Xu Shiyu Xu Thomas Yi Wojciech Zbijewski Funding This work was support, in part, by an academic-industry partnership grant from Elekta. The I-STAR Laboratory (istar.jhu.edu) and The AIAI Laboratory (aiai.jhu.edu) Department of Biomedical Engineering Johns Hopkins University 1 Amir Pourmorteza Fully 3D Recon 2015 [email protected] May 31 -June 4 Sequential Imaging: IGRT Planning MDCT Subsequent Cone-Beam CTs . High-fidelity data Low-fidelity data High exposure Less radiation exposure per scan Sequential Imaging: IGRT Planning MDCT Subsequent Cone-Beam CTs . High-fidelity data Low-fidelity data High exposure Less radiation exposure per scan The I-STAR Laboratory (istar.jhu.edu) and The AIAI Laboratory (aiai.jhu.edu) Department of Biomedical Engineering Johns Hopkins University 2 Amir Pourmorteza Fully 3D Recon 2015 [email protected] May 31 -June 4 Sequential Imaging: Brain Perfusion and Cardiac CT Low-fidelity High-fidelity Low exposure High exposure Video from: J. C. Rios, M. Luttrull, E. G. Stein, L. N. Tanenbaum.Time resolved - 4D CT Angiography: Applications and Protocols. ECR 2011 Sequential Imaging and Prior Knowledge • Prior-image-based reconstruction : – Prior image in regularization term • PICCS*: Prior Image Constrained Compressed Sensing • PIRPLE**: Prior Image Registration in Penalized Likelihood Estimation – Prior image in data fit term • Reconstruction of Difference (RoD) • The primary objective in some sequential imaging studies is to assess the difference in anatomy. *: Chen, Guang-Hong, Jie Tang, and Shuai Leng. "Prior image constrained compressed sensing (PICCS): a method to accurately reconstruct dynamic CT images from highly undersampled projection data sets." Medical physics 35.2 (2008): 660-663. **: Stayman, J. Webster, et al. "PIRPLE: a penalized-likelihood framework for incorporation of prior images in CT reconstruction." Physics in medicine and biology 58.21 (2013): 7563. The I-STAR Laboratory (istar.jhu.edu) and The AIAI Laboratory (aiai.jhu.edu) Department of Biomedical Engineering Johns Hopkins University 3 Amir Pourmorteza Fully 3D Recon 2015 [email protected] May 31 -June 4 Difference Model for the Image Volume = + ∆ Current Anatomy Prior Anatomy Change in Anatomy 0.03 ∆ 0.025 0.02 0.015 0.01 0.005 0 Difference Model for the Image Volume = W + ∆ Current Anatomy Prior Anatomy Change in Anatomy 0.03 ∆ 0.025 0.02 0.015 0.01 0.005 0 The I-STAR Laboratory (istar.jhu.edu) and The AIAI Laboratory (aiai.jhu.edu) Department of Biomedical Engineering Johns Hopkins University 4 Amir Pourmorteza Fully 3D Recon 2015 [email protected] May 31 -June 4 Image Reconstruction using Prior Images PIRPLE • Integrates prior image through a penalty term. {̂, } = argmin − ; + ∥Ψ∥1 + ∥Ψ − ∥1 ∈ℝ Data Fit Term Roughness Prior Image Registration Penalty term Penalty Term Reconstruction of Difference (RoD) • Integrates prior image/projections through the forward model. {̂∆, } = argmin − ∆, ; , + ∥Ψ∆∥1 + ∥∆∥1 ∆∈ℝ Data Fit Term Roughness Prior Magnitude Penalty term Penalty Term Image Reconstruction using Prior Images PIRPLE • Integrates prior image through a penalty term. {̂, } = argmin − ; + ∥Ψ∥1 + ∥Ψ − ∥1 ∈ℝ Data Fit Term Roughness Prior Image Registration Penalty term Penalty Term Reconstruction of Difference (RoD) • Integrates prior image/projections through the forward model. {̂∆, } = argmin − ∆, ; , + ∥Ψ∆∥1 + ∥∆∥1 ∆∈ℝ Data Fit Term Roughness Prior Magnitude Penalty term Penalty Term The I-STAR Laboratory (istar.jhu.edu) and The AIAI Laboratory (aiai.jhu.edu) Department of Biomedical Engineering Johns Hopkins University 5 Amir Pourmorteza Fully 3D Recon 2015 [email protected] May 31 -June 4 Objective Function Optimization Forward Model: = − = W + ∆ = −∆ −W Registration update Image update = ℎ(∆) . −W = . −∆ = arg min Φ ; , , = arg min Φ ∆; , , ∈ℝ ∆∈ℝ ** find using 3D-2D find ∆ using OS-SPS registration, and BFGS * Φ(∆, ; , ) = − ∆, ; , + ∥Ψ∆∥1 + ∥∆∥1 *: Stayman, J. Webster, et al. "Model-based tomographic reconstruction of objects containing known components." Medical Imaging, IEEE Transactions on 31.10 (2012): 1837-1848. **: Erdogan, Hakan, and Jeffrey A. Fessler. "Ordered subsets algorithms for transmission tomography." PMB, 44.11 (1999): 2835. Objective Function Optimization Forward Model: = − = W + ∆ = −∆ −W Registration update Image update = ℎ(∆) . −W = . −∆ = arg min Φ ; , , = arg min Φ ∆; , , ∈ℝ ∆∈ℝ ** find using 3D-2D find ∆ using OS-SPS registration, and BFGS * Φ(∆, ; , ) = − ∆, ; , + ∥Ψ∆∥1 + ∥∆∥1 *: Stayman, J. Webster, et al. "Model-based tomographic reconstruction of objects containing known components." Medical Imaging, IEEE Transactions on 31.10 (2012): 1837-1848. **: Erdogan, Hakan, and Jeffrey A. Fessler. "Ordered subsets algorithms for transmission tomography." PMB, 44.11 (1999): 2835. The I-STAR Laboratory (istar.jhu.edu) and The AIAI Laboratory (aiai.jhu.edu) Department of Biomedical Engineering Johns Hopkins University 6 Amir Pourmorteza Fully 3D Recon 2015 [email protected] May 31 -June 4 Objective Function Optimization Forward Model: = − = W + ∆ = −∆ −W Registration update Image update = ℎ(∆) . −W = . −∆ = arg min Φ ; , , = arg min Φ ∆; , , ∈ℝ ∆∈ℝ ** find using 3D-2D find ∆ using OS-SPS registration, and BFGS * Φ(∆, ; , ) = − ∆, ; , + ∥Ψ∆∥1 + ∥∆∥1 *: Stayman, J. Webster, et al. "Model-based tomographic reconstruction of objects containing known components." Medical Imaging, IEEE Transactions on 31.10 (2012): 1837-1848. **: Erdogan, Hakan, and Jeffrey A. Fessler. "Ordered subsets algorithms for transmission tomography." PMB, 44.11 (1999): 2835. Digital Phantom • Digital Phantom: Derived from high-fidelity CBCT data • New measurements made from: Prior + tumor • spherical tumor – 10.5 mm diameter – Attenuation 0.020 mm-1 • C-Arm Geometry: SAD = 77.5, SDD = 118.3 cm, 720 projections over 360° • Poisson measurement noise: b = 102 : 101/2 : 105 (photons) + = Prior Tumor New measurements The I-STAR Laboratory (istar.jhu.edu) and The AIAI Laboratory (aiai.jhu.edu) Department of Biomedical Engineering Johns Hopkins University 7 Amir Pourmorteza Fully 3D Recon 2015 [email protected] May 31 -June 4 Penalty coefficient optimization ReconstructedI =10000 # projections:180 Difference I =10000 RMSE # projections:180 0 0 -3 x 10 0.02 4.5 4.5 2.5 4 0.015 4 Magnitude ∥ ∥ 3.5 3.5 2 ∆ 1 0.01 3 3 ) ) M M 1.5 ( ( 2.5 0.005 2.5 10 10 log log 2 2 0 1 1.5 1.5 * 1 -0.005 1 0.5 0.5 0.5 -0.01 0.5 1 1.5 2 2.5 0.5 1 1.5 2 2.5 log ( ) log ( ) 10 R Roughness ∥Ψ∆∥1 10 R Local vs. Global Acquisition/Reconstruction • If difference is spatially limited – ∆ is negligible outside VOI • Local Reconstruction – Usually not possible in Model-Based Reconstruction – Computational speedup ∆ • Local (truncated) Acquisition – Radiation dose reduction 1 = −W −∆ The I-STAR Laboratory (istar.jhu.edu) and The AIAI Laboratory (aiai.jhu.edu) Department of Biomedical Engineering Johns Hopkins University 8 Amir Pourmorteza Fully 3D Recon 2015 [email protected] May 31 -June 4 Global vs. Local Acquisition Global RoD Local RoD 0.045 0.04 0.035 0.03 0.025 0.02 0.015 0.01 0.005 -3 x 10 ̂∆ + 12 10 8 6 4 2 Fluence = 104 (photons) ̂∆ 0 180 projections RMSE: 4.19 4.02 ×10-4 mm-1 Performance: Sparse Acquisitions -3 x 10 5 PL RoD 4 ) 1 - 3 2 RMSE RMSE (mm 1 Fluence= 104 (photons) 0 0 100 200 300 400 # of projections PL 0.045 0.04 ̂ 0.035 0.03 0.025 RoD 0.02 0.015 ̂∆ + 0.01 0.005 16 24 45 90 180 360 The I-STAR Laboratory (istar.jhu.edu) and The AIAI Laboratory (aiai.jhu.edu) Department of Biomedical Engineering Johns Hopkins University 9 Amir Pourmorteza Fully 3D Recon 2015 [email protected] May 31 -June 4 Performance: Sparse Acquisitions -3 x 10 5 PL RoD 4 ) 1 - 3 2 RMSE RMSE (mm 1 Fluence= 104 (photons) 0 0 100 200 300 400 # of projections 0.03 PL 0.045 0.04 0.02 0.035 ̂ − 0.010.03 0.025 RoD 0 0.02 -0.010.015 ̂∆ 0.01 -0.02 0.005 16 24 45 90 180 360 Performance: Varying Fluence -3 6 x 10 PL 5 RoD ) 1 - 4 (mm 3 2 RMSE 1 # of projections: 90 0 2 3 4 5 10 10 10 10 Incident Fluence 0.03 PL 0.045 0.020.04 0.035 0.01 0.03 00.025 RoD 0.02 -0.01 0.015 + ∆ -0.020.01 0.005 -0.03 102 105 (photons) The I-STAR Laboratory (istar.jhu.edu) and The AIAI Laboratory (aiai.jhu.edu) Department of Biomedical Engineering Johns Hopkins University 10 Amir Pourmorteza Fully 3D Recon 2015 [email protected] May 31 -June 4 Performance: Varying Fluence -3 6 x 10 PL 5 RoD ) 1 - 4 3 2 RMSE RMSE (mm 1 # of projections: 90 0 2 3 4 5 10 10 10 10 Incident Fluence 0.03 PL 0.02 − 0.01 0 RoD -0.01 ∆ -0.02 -0.03 102 105 (photons) Performance of Likelihood-based Registration • Prior image transformed by a known rigid transform.
Load more

Recommended publications
  • Medical Physics</I>
    Anniversary Paper: Development of x-ray computed tomography: The role of Medical Physics and AAPM from the 1970s to present ͒ Xiaochuan Pana Department of Radiology, University of Chicago, Chicago, Illinois 60637 Jeffrey Siewerdsen Ontario Cancer Institute, Princess Margaret Hospital, Toronto, Ontario M5G 2M9, Canada and Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 2M9, Canada Patrick J. La Riviere Department of Radiology, University of Chicago, Chicago, Illinois 60637 Willi A. Kalender Institute of Medical Physics, University Erlangen-Nuernberg, 91052 Erlangen, Germany ͑Received 7 April 2008; revised 9 June 2008; accepted for publication 9 June 2008; published 22 July 2008͒ The AAPM, through its members, meetings, and its flagship journal Medical Physics, has played an important role in the development and growth of x-ray tomography in the last 50 years. From a spate of early articles in the 1970s characterizing the first commercial computed tomography ͑CT͒ scanners through the “slice wars” of the 1990s and 2000s, the history of CT and related techniques such as tomosynthesis can readily be traced through the pages of Medical Physics and the annals of the AAPM and RSNA/AAPM Annual Meetings. In this article, the authors intend to give a brief review of the role of Medical Physics and the AAPM in CT and tomosynthesis imaging over the last few decades. © 2008 American Association of Physicists in Medicine. ͓DOI: 10.1118/1.2952653͔ Key words: computed tomography, tomosynthesis I. INTRODUCTION duction of CT in 1972 by EMI, and then trailing off through the 1980s as the technology matured and emerging technolo- As the AAPM celebrates its 50th anniversary, it is natural to gies, such as magnetic resonance imaging ͑MRI͒, won atten- pause and take stock of the contribution its members, meet- tion from researchers and clinicians alike.
    [Show full text]
  • Performance Cone-Beam Ct of the Head
    IMAGE QUALITY, MODELING, AND DESIGN FOR HIGH- PERFORMANCE CONE-BEAM CT OF THE HEAD by Jennifer Xu A dissertation submitted to Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland December, 2016 © Jennifer Xu 2016 All rights reserved Abstract Diagnosis and treatment of neurological and otolaryngological diseases rely heavily on visualization of fine, subtle anatomical structures in the head. In particular, high-quality head imaging at the point of care mitigates patient risk associated with transport and decreases time to diagnosis for time-sensitive diseases. Cone-beam computed tomography (CBCT) systems have found widespread adoption in diagnostic and image-guided procedures. Such systems exhibit potential for adaptation as point-of-care systems due to relatively low cost, mechanical simplicity, and inherently high spatial resolution, but are generally challenged by low contrast imaging tasks (e.g., visualization of tumors or hemorrhages). This thesis details the development and design of a CBCT imaging system with performance sufficient for high-quality imaging of the head and suitable to deployment at the point of care. The performance of a commercially available head-and-neck CBCT scanner was assessed to determine the potential of such systems for high-quality head imaging. Results indicated low-contrast visualization was challenged by high detector noise and scatter. Photon counting x-ray detectors (PCDs) were identified as a potential technology that could improve the low-contrast visualization, and an imaging performance model was developed to quantify their imaging performance. The model revealed important implications for energy resolution, noise, and spatial resolution as a function of energy threshold and charge sharing rejection.
    [Show full text]
  • American Association of Physicists in Medicine Awards Ceremony
    American Association of Physicists in Medicine Awards Ceremony July 30, 2012 Ballroom CD Charlotte Convention Center Charlotte, North Carolina 6:30 p.m. The American Association of Physicists in Medicine is the premier organization in medical physics, a broadly-based scientific and professional discipline encompassing physics principles and applications in biology and medicine. The mission of the American Association of Physicists in Medicine is to advance the science, education and professional practice of medical physics. 2012 Program Welcome and Presentation of Awards Gary A. Ezzell, Ph.D. AAPM President Honoring Deceased AAPM Members AAPM Fellowships and Grants Research Seed Funding Initiative Journal of Applied Clinical Medical Physics Paper Awards AAPM-IPEM Medical Physics Travel Grant Jack Fowler Junior Investigator Award John R. Cameron Young Investigator Awards AAPM Award for Innovation in Medical Physics Teaching Farrington Daniels Award Sylvia Sorkin Greenfield Award Fellows Recognition of 50+ Years of AAPM Membership Marvin M. D. Williams Professional Achievement Award Edith H. Quimby Lifetime Achievement Award William D. Coolidge Award Closing Remarks Reception immediately following ~ AAPM Fellowships and Grants ~ AAPM Fellowship for Graduate Study in Medical Physics ~ The fellowship is awarded for the first two years of graduate study leading to a doctoral degree in Medical Physics. A stipend of $13,000 per year, plus tuition support not exceeding $5,000 per year is assigned to the recipient. The amount of tuition support granted will be at the discretion of the AAPM. The award will be paid to the recipient’s institution and distributed in accordance with the institution’s disbursement procedures. It is AAPM’s policy that none of the funds may be diverted to the institution’s “facilities”, “administrative”, or other overhead categories and the full $13,000 stipend must be provided to the recipient.
    [Show full text]
  • Advanced System Models for Reconstruction in Flat-Panel Detector Cone-Beam CT
    Steven Tilley ([email protected]) Fully 3D Recon 2015 May 31 -June 4 Fully3D Advanced System Models for Reconstruction in Flat-Panel Detector Cone-Beam CT Steven Tilley, Jeffrey Siewerdsen, Web Stayman Department of Biomedical Engineering Johns Hopkins University Schools of Medicine and Engineering Acknowledgements AIAI Laboratory Advanced Imaging Algorithms and Instrumentation Lab aiai.jhu.edu [email protected] I-STAR Laboratory Imaging for Surgery, Therapy, and Radiology istar.jhu.edu [email protected] Faculty and Scientists Students Industry Partners Tharindu De Silva Qian Cao Sungwon Yoon Grace Gang Hao Dang Kevin Holt Aswin Mathews Sarah Ouadah David Nisius Amir Pourmorteza Sureerat Reaungamornrat Edward Shapiro Jeffrey Siewerdsen Steven Tilley II Alejandro Sisniega Ali Uneri Shiyu Xu Jennifer Xu Wojciech Zbijewski Thomas Yi Funding Supported in part by a Varian industry partnership and NIH grants R21-EB-014964 and T32-EB010021 This work was supported, in part, by the above grants. The contents of this presentation are solely the responsibility of the authors and do not necessarily represent the official view of Johns Hopkins or the NIH. The I-STAR Laboratory (istar.jhu.edu) and The AIAI Laboratory (aiai.jhu.edu) Department of Biomedical Engineering Johns Hopkins University 1 Steven Tilley ([email protected]) Fully 3D Recon 2015 May 31 -June 4 Noise model and reality mismatch Normalized Detector Units Detector Normalized Units Detector Normalized Source and Detector Blur Modeling Mean: 푔 푦 0 = 퐁푠퐃 푔 exp(−퐀휇) 푦 = 퐁푑퐁푠퐃 푔 exp(−퐀휇)
    [Show full text]
  • Image-Guided Interventions Terry Peters • Kevin Cleary Editors
    Image-Guided Interventions Terry Peters • Kevin Cleary Editors Image-Guided Interventions Technology and Applications Editors Terry Peters Kevin Cleary Imaging Research Laboratories Radiology Department Robarts Research Institute Imaging Science and Information University of Western Ontario Systems (ISIS) Center 100 Perth Drive 2115 Wisconsin Ave. NW, Suite 603 London, ON N6A 5K8 Washington, DC 20057 Canada USA ISBN: 978-0-387-73856-7 e-ISBN: 978-0-387-73858-1 Library of Congress Control Number: 2007943573 © 2008 Springer Science+Business Media, LLC All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Springer Science+Business Media, LLC or the author(s) make no warranty or representation, either express or implied, with respect to this DVD or book, including their quality, mechantability, or fitness for a particular purpose. In no event will Springer Science+Business Media, LLC or the author(s) be liable for direct, indirect, special, incidental, or consequential damages arising out of the use or inability to use the disc or book, even if Springer Science+Business Media, LLC or the author(s) has been advised of the possibility of such damages.
    [Show full text]
  • Medical Imaging & Case Reports
    Scientific UNITED Group International Conference on Medical Imaging & Case Reports October 29-31, 2018 DoubleTree by Hilton Baltimore - BWI Airport 890 Elkridge Landing Rd, Linthicum Heights, MD 21090, USA www.unitedscientificgroup.com/conferences/medical-imaging/ [email protected] INDEX « Keynote Presentations .......05 - 16 « Featured Presentations .......17 - 64 « Poster Presentations .......67 - 76 « About Organizer .......78 - 79 October 29 1MONDAY Keynotes Session Keynote Session Expanding Frontiers of Neuroimaging: Dynamic Molecular Imaging Rajendra D. Badgaiyan Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY Abstract Lack of a sensitive method for detection of acute changes in neurotransmission has limited the scope of Neuroimaging research because neurotransmitters play an important role in regulation of cognitive and behavioral functions. We recently developed a technique to detect, map and measure dopamine released acutely during cognitive or behavioral processing. The technique is called neurotransmitter imaging or single scan dynamic molecular imaging technique (SDMIT). It exploits the competition between a neurotransmitter and its receptor ligand for occupancy of the same receptor site. In this technique after patients are positioned in the positron emission tomography (PET) camera, a radio-labeled neurotransmitter ligand is injected intravenously, and the PET data acquisition started. These data are used by a receptor kinetic model to detect, map and measure neurotransmitter released dynamically in different brain areas. Patients are asked to perform a cognitive task while in the scanner and the amount of neurotransmitter released in different brain areas measured. By comparing it with the data acquired in healthy volunteers during performance of a similar task, it is possible to determine whether a neurotransmitter release is dysregulated in the patients and whether the dysregulation is responsible for clinical symptoms.
    [Show full text]
  • Cone-Beam Computed Tomography for Neuro-Angiographic Imaging
    CONE-BEAM COMPUTED TOMOGRAPHY FOR NEURO-ANGIOGRAPHIC IMAGING by Michael Mow A dissertation submitted to Johns Hopkins University in conformity with the requirements for the degree of Master of Science in Engineering Baltimore, Maryland May 2017 © 2017 Michael Mow All Rights Reserved Abstract Accurate and timely diagnosis and treatment of head trauma incidents, particularly ischemic stroke, rely on confident visualization of brain vasculature and accurate measurements of flow characteristics. Due to their low cost, high spatial resolution, small footprint, and adaptable geometry, cone-beam computed tomography (CBCT) systems have shown to be valuable for point of care applications that require timely diagnosis. However, image quality in CBCT scanners are potentially limited by slow rotation speed and are therefore challenged in the context of hemodynamic neurovascular imaging, as in CT Angiography (CTA) and CT Perfusion (CTP). This thesis details the advancement of neuro- angiographic imaging in CBCT systems using prior-image based reconstruction methods such as Reconstruction-of-Difference (RoD) to provide accurate visualization of cerebral vasculature despite slow image acquisition and/or sparse projection data. The performance of a novel CBCT system for high quality neuro- angiographic imaging was assessed using RoD, a prior-image-based reconstruction method. A digital simulation framework is presented that involves dynamic vasculature models and an accelerated forward projection method. Results indicate feasibility for CBCT angiography attained with a 5 second scan time, despite a limited number of projections (“sparse” projection data). Preliminary results in CTP imaging demonstrate the potential for perfusion parameter estimation and warrant future research using a 3D printed vessel phantom developed in this work.
    [Show full text]
  • Reconstruction Across Imaging Modalities: MRI Introduction To
    7/30/2018 Reconstruction across imaging modalities: MRI Brad Sutton [email protected] Bioengineering and Beckman Institute Introduction to Spins and Classical MRI Physics Most MRI scans are looking at hydrogen nucleus. N This is good: Body is + mostly water H2O H Other nuclei are available in MRI: 13C, 19F, 23Na, S others Spinning proton == SPIN Spinning proton has a magnetic moment :: Classical Description: Behaves as a bar magnet. 1 7/30/2018 Sample outside the MRI magnet, spins randomly oriented. Place sample in the MRI magnet… N Static Field ON S Net MRI Magnetic Moment 2 7/30/2018 From spins to signal: Net magnetic moment from spins N Static Field ON N S RF When tipped away from the S main field, then begins to precess. Precesses at a frequency proportional to the magnetic field strength. At 3 T = 128 MHz Localization in Space: Larmor Precession Since frequency is proportional magnetic field strength if we apply a magnetic field that varies with spatial position, the precession frequency varies with spatial position. B Mag. Field Low Frequency Low Frequency Strength Object High Frequency High Frequency x Position x Position From Noll: fMRI Primer: http://fmri.research.umich.edu/documents/fmri_primer.pdf 3 7/30/2018 Magnetic Field Strength Spatial position RECEIVED SIGNAL IS SUM OF ALL THESE SIGNALS. Fourier Image Reconstruction (1D) Low Frequency MR Signal Object Fourier Transform High Frequency time 1D Image x Position Projection similar to CT! From Noll: fMRI Primer: http://fmri.research.umich.edu/documents/fmri_primer.pdf 4
    [Show full text]
  • Nass 2017 Annual Report
    NASS 2017 ANNUAL REPORT President’s Message . 2 Health Policy & Reimbursement . 20 2016-17 Board of Directors . 3 Governance Committee . 22 Membership . 4 Spine Education & Research Center . 22 Meeting Services . 5 Publications . 23 Education . 6 Spine Foundation . 25 Video Department . 11 2017 Recognition Awards . 26 Advocacy . 12 2016 NASS Committees . 28 Ethics & Professionalism . 16 Donor Recognition . 33 Research . 17 Financials . 37 PRESIDENT’S MESSAGE NASS 2017 ANNUAL REPORT 2 “If a cluttered desk is the sign NASS has also achieved a reputation as an excellent of a cluttered mind, of what, resource for meeting management . This year, NASS was then is an empty desk a sign?” contracted by the McKenzie Institute international and the International Society of Minimally Invasive Spine Surgery to -A . Einstein manage their annual meetings . My desk is much less cluttered now NASS’ expertise continues to be in demand from a policy than when I was serving as the 33rd and reimbursement standpoint, as well . Collaborating with President of NASS . Despite this eviCore, an insurance management firm that manages F. Todd Wetzel, MD obvious handicap, I was asked to more than 100 million patients, the Payor Policy Review NASS President write the introduction to this annual 2016-17 Committee is reviewing 21 draft policies for spine surgery report . and spine injections . eviCore also has expressed interest in reviewing NASS coverage recommendations as well . This This is not as easy as it seems . Every year NASS surpasses is hardly surprising as our Coverage Recommendations itself . This last year was no exception . Unfortunately, program continues to grow . The coverage documents limitations of space and time preclude me from mentioning have proven to be a valuable resource for NASS members every individual effort and every program in the detail as well, with nearly 4,000 chapter downloads by NASS they deserve .
    [Show full text]
  • Sunday, July 25, 2021 Sunday, July 25, 2021
    Program of the Meeting CALENDAR OF EVENTS * Presenting Author Sunday, July 25, 2021 Sunday, July 25, 2021 Council Symposium SAM Multi-Disciplinary Scientific Symposium 10:30 am - 11:30 am 10:30 am - 11:30 am -TRACK 1 -TRACK 4 SU-A-TRACK 1 International Council Symposium: AAPM SU-A-TRACK 4 Solid State PET in Radiology and Global Engagement; Planning for the Future Radiation Oncology: from SiPM to AI in the Clinic Moderator: Ana Maria Marques da Silva, Pontifica Universidade Moderator: Jun Zhang, The Ohio State University, Columbus, OH Catolica do RS, Porto Alegre, RS 10:30 am J. Zhang, The Ohio State University: Technologies and AI 10:30 am S. Avery, University of Pennsylvania: Global Medical Features of SiPM PET Instrumentation Physics Education and Training 10:55 am S. Bowen, University of Washington, School of Medicine: 10:38 am S. Parker, Wake Forest Baptist Health High Point Medical Clinical Considerations of SiPM PET in Radiology and Center: Global Need Assessment Radiation Oncology 10:46 am J. Palta, Virginia Commonwealth University: Global 11:20 am Q&A & Panel Discussion Collaborations 10:54 am R. Jeraj, University of Wisconsin: Global Research and SAM Therapy Scientific Symposium Scientific Innovation 10:30 am - 12:30 pm 11:02 am G. Kim, University of California, San Diego: Global Data and Information Exchange -TRACK 5 11:10 am S. Wadi-Ramahi, University of Pittsburgh Medical Center: SU-AB-TRACK 5 Affordable Cancer Care for All Global Clinical Education and Training Moderator: Laurence Edward Court, University of Texas MD 11:18 am Q&A Anderson Cancer Center, Houston, TX 10:30 am Introduction Students and Trainees 10:33 am C.
    [Show full text]
  • Thesis Was Performed at the Netherlands Cancer Institute – Antoni Van Leeuwenhoek Hospital, Department of Radiation Oncology, Amsterdam, the Netherlands
    UvA-DARE (Digital Academic Repository) Towards image-guided radiotherapy of prostate cancer Smitsmans, M.H.P. Publication date 2010 Document Version Final published version Link to publication Citation for published version (APA): Smitsmans, M. H. P. (2010). Towards image-guided radiotherapy of prostate cancer. The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital. General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl) Download date:24 Sep 2021 TOWARDS IMAGE-GUIDED RADIOTHERAPY OF PROSTATE CANCER Monique Helene Paola Smitsmans TOWARDS IMAGE-GUIDED RADIOTHERAPY OF PROSTATE CANCER ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. D.C. van den Boom ten overstaan van een door het college voor promoties ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel op dinsdag 12 oktober 2010, te 12:00 uur door Monique Helene Paola Smitsmans geboren te Heerlen PROMOTIECOMMISSIE PROMOTOR Prof.
    [Show full text]
  • Study of Novel Techniques for Verification Irnaging and Patient Dose Reconstruction in External Bearn Radiation Therapy
    Study of Novel Techniques for Verification Irnaging and Patient Dose Reconstruction in External Bearn Radiation Therapy Geneviève Jarry Doctor of Philosophy Department of Physics McGill University Montreal, Quebee 2007-03-29 A thesis submitted to the faculty of graduate studies and researeh in partial fulfillment of the requirements of the degree of Doctor of Philosophy ©Geneviève Jarry 2006 Library and Bibliothèque et 1+1 Archives Canada Archives Canada Published Heritage Direction du Branch Patrimoine de l'édition 395 Wellington Street 395, rue Wellington Ottawa ON K1A ON4 Ottawa ON K1A ON4 Canada Canada Your file Votre référence ISBN: 978-0-494-32300-7 Our file Notre référence ISBN: 978-0-494-32300-7 NOTICE: AVIS: The author has granted a non­ L'auteur a accordé une licence non exclusive exclusive license allowing Library permettant à la Bibliothèque et Archives and Archives Canada to reproduce, Canada de reproduire, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par télécommunication ou par l'Internet, prêter, telecommunication or on the Internet, distribuer et vendre des thèses partout dans loan, distribute and sell th es es le monde, à des fins commerciales ou autres, worldwide, for commercial or non­ sur support microforme, papier, électronique commercial purposes, in microform, et/ou autres formats. paper, electronic and/or any other formats. The author retains copyright L'auteur conserve la propriété du droit d'auteur ownership and moral rights in et des droits moraux qui protège cette thèse. this thesis. Neither the thesis Ni la thèse ni des extraits substantiels de nor substantial extracts from it celle-ci ne doivent être imprimés ou autrement may be printed or otherwise reproduits sans son autorisation.
    [Show full text]