Search Results - "Delfino, Jana G"

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    MRI‐related FDA adverse event reports: A 10‐yr review by Delfino, Jana G., Krainak, Daniel M., Flesher, Stephanie A., Miller, Donald L.

    Published in Medical physics (Lancaster) (01-12-2019)
    “…Purpose To provide an overview of the types of adverse events reported to the US Food and Drug Administration (US FDA) for magnetic resonance (MR) systems over…”
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    Evaluating Machine Learning-Based MRI Reconstruction Using Digital Image Quality Phantoms by Tan, Fei, Delfino, Jana G, Zeng, Rongping

    Published in Bioengineering (Basel) (01-06-2024)
    “…Quantitative and objective evaluation tools are essential for assessing the performance of machine learning (ML)-based magnetic resonance imaging (MRI)…”
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    Cardiovascular magnetic resonance at 3.0T: Current state of the art by Oshinski, John N, Delfino, Jana G, Sharma, Puneet, Gharib, Ahmed M, Pettigrew, Roderic I

    “…There are advantages to conducting cardiovascular magnetic resonance (CMR) studies at a field strength of 3.0 Telsa, including the increase in bulk…”
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    Determination of transmural, endocardial, and epicardial radial strain and strain rate from phase contrast MR velocity data by Delfino, Jana G., Fornwalt, Brandon K., Eisner, Robert L., Leon, Angel R., Oshinski, John N.

    Published in Journal of magnetic resonance imaging (01-03-2008)
    “…Purpose To develop a method for computing radial strain (ε) and strain rate (SR) from phase contrast magnetic resonance (PCMR) myocardial tissue velocity data…”
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    Challenges in ensuring the generalizability of image quantitation methods for MRI by Keenan, Kathryn E., Delfino, Jana G., Jordanova, Kalina V., Poorman, Megan E., Chirra, Prathyush, Chaudhari, Akshay S., Baessler, Bettina, Winfield, Jessica, Viswanath, Satish E., deSouza, Nandita M.

    Published in Medical physics (Lancaster) (01-04-2022)
    “…Image quantitation methods including quantitative MRI, multiparametric MRI, and radiomics offer great promise for clinical use. However, many of these methods…”
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    Multiparametric Quantitative Imaging Biomarker as a Multivariate Descriptor of Health: A Roadmap by Raunig, David L., Pennello, Gene A., Delfino, Jana G., Buckler, Andrew J., Hall, Timothy J., Guimaraes, Alexander R., Wang, Xiaofeng, Huang, Erich P., Barnhart, Huiman X., deSouza, Nandita, Obuchowski, Nancy

    Published in Academic radiology (01-02-2023)
    “…Multiparametric quantitative imaging biomarkers (QIBs) offer distinct advantages over single, univariate descriptors because they provide a more complete…”
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    An FDA Guide on Indications for Use and Device Reporting of Artificial Intelligence-Enabled Devices: Significance for Pediatric Use by Nelson, Brandon J., Zeng, Rongping, Sammer, Marla B.K., Frush, Donald P., Delfino, Jana G.

    “…Radiology has been a pioneer in adopting artificial intelligence (AI)-enabled devices into the clinic. However, initial clinical experience has identified…”
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    Multiparametric Quantitative Imaging Biomarkers for Phenotype Classification: A Framework for Development and Validation by Delfino, Jana G., Pennello, Gene A., Barnhart, Huiman X., Buckler, Andrew J., Wang, Xiaofeng, Huang, Erich P., Raunig, Dave L., Guimaraes, Alexander R., Hall, Timothy J., deSouza, Nandita M., Obuchowski, Nancy

    Published in Academic radiology (01-02-2023)
    “…This manuscript is the third in a five-part series related to statistical assessment methodology for technical performance of multi-parametric quantitative…”
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    Applying queueing theory to evaluate wait-time-savings of triage algorithms by Thompson, Yee Lam Elim, Levine, Gary M., Chen, Weijie, Sahiner, Berkman, Li, Qin, Petrick, Nicholas, Delfino, Jana G., Lago, Miguel A., Cao, Qian, Samuelson, Frank W.

    Published in Queueing systems (2024)
    “…In the past decade, artificial intelligence (AI) algorithms have made promising impacts in many areas of healthcare. One application is AI-enabled…”
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    Regulatory considerations for medical imaging AI/ML devices in the United States: concepts and challenges by Petrick, Nicholas, Chen, Weijie, Delfino, Jana G., Gallas, Brandon D., Kang, Yanna, Krainak, Daniel, Sahiner, Berkman, Samala, Ravi K.

    “…To introduce developers to medical device regulatory processes and data considerations in artificial intelligence and machine learning (AI/ML) device…”
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    Response to Standardized MR Terminology and Reporting of Implants and Devices as Recommended by the American College of Radiology Subcommittee on MR Safety by Woods, Terry O, Delfino, Jana G, Shein, Mitchell J

    Published in Radiology (01-06-2016)
    “…The U.S. Food and Drug Administration (FDA) continually works toward the goal of safety. For patients with magnetic resonance (MR) Conditional devices, safety…”
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    Risks of MRI in Patients with a Pacemaker or Defibrillator by Delfino, Jana G, Viohl, Ingmar, Woods, Terry O, Russo, Robert J, Lampert, Rachel, Birgersdotter-Green, Ulrika

    Published in The New England journal of medicine (22-06-2017)
    “…To the Editor: Russo et al. (Feb. 23 issue) 1 and others 2 have studied the risks of magnetic resonance imaging (MRI) in patients with “legacy” pacemakers or…”
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