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  1. Article ; Online: Deep learning-based rapid image reconstruction and motion correction for high-resolution cartesian first-pass myocardial perfusion imaging at 3T.

    Wang, Junyu / Salerno, Michael

    Magnetic resonance in medicine

    2024  

    Abstract: Purpose: To develop and evaluate a deep learning (DL) -based rapid image reconstruction and motion correction technique for high-resolution Cartesian first-pass myocardial perfusion imaging at 3T with whole-heart coverage for both single-slice (SS) and ... ...

    Abstract Purpose: To develop and evaluate a deep learning (DL) -based rapid image reconstruction and motion correction technique for high-resolution Cartesian first-pass myocardial perfusion imaging at 3T with whole-heart coverage for both single-slice (SS) and simultaneous multi-slice (SMS) acquisitions.
    Methods: 3D physics-driven unrolled network architectures were utilized for the reconstruction of high-resolution Cartesian perfusion imaging. The SS and SMS multiband (MB) = 2 networks were trained from 135 slices from 20 subjects. Structural similarity index (SSIM), peak SNR (PSNR), and normalized RMS error (NRMSE) were assessed, and prospective images were blindly graded by two experienced cardiologists (5, excellent; 1, poor). For respiratory motion correction, a 2D U-Net based motion corrected network was proposed, and the temporal fidelity and second-order derivative were calculated to assess the performance of the motion correction.
    Results: Excellent performance was demonstrated in the proposed technique with high SSIM and PSNR, and low NRMSE. Image quality scores were (4.3 [4.3, 4.4], 4.5 [4.4, 4.6], 4.3 [4.3, 4.4], and 4.5 [4.3, 4.5]) for SS DL and SS L1-SENSE, MB = 2 DL and MB = 2 SMS-L1-SENSE, respectively, showing no statistically significant difference (p > 0.05 for SS and SMS) between (SMS)-L1-SENSE and the proposed DL technique. The network inference time was around 4 s per dynamic perfusion series with 40 frames while the time of (SMS)-L1-SENSE with GPU acceleration was approximately 30 min.
    Conclusion: The proposed DL-based image reconstruction and motion correction technique enabled rapid and high-quality reconstruction for SS and SMS MB = 2 high-resolution Cartesian first-pass perfusion imaging at 3T.
    Language English
    Publishing date 2024-04-04
    Publishing country United States
    Document type Journal Article
    ZDB-ID 605774-3
    ISSN 1522-2594 ; 0740-3194
    ISSN (online) 1522-2594
    ISSN 0740-3194
    DOI 10.1002/mrm.30106
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Seeing the Unseen in Cardiac Remodeling: Cardiac Diffusion Tensor Imaging as a Structural Biomarker in STEMI.

    Ennis, Daniel B / Salerno, Michael

    JACC. Cardiovascular imaging

    2023  Volume 16, Issue 2, Page(s) 172–174

    MeSH term(s) Humans ; ST Elevation Myocardial Infarction/diagnostic imaging ; ST Elevation Myocardial Infarction/therapy ; Diffusion Tensor Imaging ; Ventricular Remodeling ; Predictive Value of Tests ; Biomarkers ; Magnetic Resonance Imaging/methods
    Chemical Substances Biomarkers
    Language English
    Publishing date 2023-01-06
    Publishing country United States
    Document type Editorial ; Research Support, Non-U.S. Gov't ; Comment
    ZDB-ID 2491503-8
    ISSN 1876-7591 ; 1936-878X
    ISSN (online) 1876-7591
    ISSN 1936-878X
    DOI 10.1016/j.jcmg.2022.12.011
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Inline Quantitative Myocardial Perfusion by CMR: Coming Online Soon?

    Salerno, Michael

    JACC. Cardiovascular imaging

    2019  Volume 12, Issue 10, Page(s) 1970–1972

    MeSH term(s) Coronary Artery Disease ; Coronary Circulation ; Humans ; Myocardial Ischemia ; Myocardial Perfusion Imaging
    Language English
    Publishing date 2019-08-14
    Publishing country United States
    Document type Editorial ; Research Support, N.I.H., Extramural ; Comment
    ZDB-ID 2491503-8
    ISSN 1876-7591 ; 1936-878X
    ISSN (online) 1876-7591
    ISSN 1936-878X
    DOI 10.1016/j.jcmg.2019.06.011
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Precision of Echocardiographic Measurements.

    Pillai, Balakrishnan / Salerno, Michael / Schnittger, Ingela / Cheng, Susan / Ouyang, David

    Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography

    2024  

    Language English
    Publishing date 2024-01-08
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1035622-8
    ISSN 1097-6795 ; 0894-7317
    ISSN (online) 1097-6795
    ISSN 0894-7317
    DOI 10.1016/j.echo.2024.01.001
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Morality, punishment, and revealing other people's secrets.

    Salerno, Jessica M / Slepian, Michael L

    Journal of personality and social psychology

    2022  Volume 122, Issue 4, Page(s) 606–633

    Abstract: Nine studies represent the first investigation into when and why people reveal other people's secrets. Although people keep their own immoral secrets to avoid being punished, we propose that people will be motivated to ... ...

    Abstract Nine studies represent the first investigation into when and why people reveal other people's secrets. Although people keep their own immoral secrets to avoid being punished, we propose that people will be motivated to reveal
    MeSH term(s) Emotions ; Humans ; Learning ; Morals ; Punishment ; Self Disclosure
    Language English
    Publishing date 2022-01-31
    Publishing country United States
    Document type Journal Article
    ZDB-ID 3103-3
    ISSN 1939-1315 ; 0022-3514
    ISSN (online) 1939-1315
    ISSN 0022-3514
    DOI 10.1037/pspa0000284
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Feature Tracking by CMR: A "Double Feature"?

    Salerno, Michael

    JACC. Cardiovascular imaging

    2017  Volume 11, Issue 2 Pt 1, Page(s) 206–208

    MeSH term(s) Magnetic Resonance Imaging, Cine ; Myocardium
    Language English
    Publishing date 2017-05-17
    Publishing country United States
    Document type Editorial ; Comment
    ZDB-ID 2491503-8
    ISSN 1876-7591 ; 1936-878X
    ISSN (online) 1876-7591
    ISSN 1936-878X
    DOI 10.1016/j.jcmg.2017.01.024
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Assessing Cardiac Remodeling in Aortic Regurgitation Using Indexed Extracellular Volume: More Than Meets the "i"?

    Salerno, Michael / Patel, Toral

    JACC. Cardiovascular imaging

    2021  Volume 14, Issue 11, Page(s) 2183–2185

    MeSH term(s) Aortic Valve Insufficiency/diagnostic imaging ; Humans ; Predictive Value of Tests ; Stroke Volume ; Ventricular Function, Left ; Ventricular Remodeling
    Language English
    Publishing date 2021-10-20
    Publishing country United States
    Document type Editorial ; Research Support, N.I.H., Extramural ; Comment
    ZDB-ID 2491503-8
    ISSN 1876-7591 ; 1936-878X
    ISSN (online) 1876-7591
    ISSN 1936-878X
    DOI 10.1016/j.jcmg.2021.06.021
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Identifying socioeconomic and biophysical factors driving forest loss in protected areas.

    Powlen, Kathryn A / Salerno, Jonathan / Jones, Kelly W / Gavin, Michael C

    Conservation biology : the journal of the Society for Conservation Biology

    2023  Volume 37, Issue 4, Page(s) e14058

    Abstract: Protected areas (PAs) are a commonly used strategy to confront forest conversion and biodiversity loss. Although determining drivers of forest loss is central to conservation success, understanding of them is limited by conventional modeling assumptions. ...

    Abstract Protected areas (PAs) are a commonly used strategy to confront forest conversion and biodiversity loss. Although determining drivers of forest loss is central to conservation success, understanding of them is limited by conventional modeling assumptions. We used random forest regression to evaluate potential drivers of deforestation in PAs in Mexico, while accounting for nonlinear relationships and higher order interactions underlying deforestation processes. Socioeconomic drivers (e.g., road density, human population density) and underlying biophysical conditions (e.g., precipitation, distance to water, elevation, slope) were stronger predictors of forest loss than PA characteristics, such as age, type, and management effectiveness. Within PA characteristics, variables reflecting collaborative and equitable management and PA size were the strongest predictors of forest loss, albeit with less explanatory power than socioeconomic and biophysical variables. In contrast to previously used methods, which typically have been based on the assumption of linear relationships, we found that the associations between most predictors and forest loss are nonlinear. Our results can inform decisions on the allocation of PA resources by strengthening management in PAs with the highest risk of deforestation and help preemptively protect key biodiversity areas that may be vulnerable to deforestation in the future.
    MeSH term(s) Humans ; Conservation of Natural Resources/methods ; Biodiversity ; Mexico ; Population Density ; Socioeconomic Factors
    Language English
    Publishing date 2023-03-05
    Publishing country United States
    Document type Journal Article
    ZDB-ID 58735-7
    ISSN 1523-1739 ; 0888-8892
    ISSN (online) 1523-1739
    ISSN 0888-8892
    DOI 10.1111/cobi.14058
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Commentary: Cardiac sarcoma-Can we win this battle?

    Magarakis, Michael / Salerno, Tomas A

    The Journal of thoracic and cardiovascular surgery

    2020  Volume 162, Issue 1, Page(s) 118–119

    MeSH term(s) Heart Neoplasms/diagnostic imaging ; Heart Neoplasms/surgery ; Humans ; Sarcoma/diagnostic imaging ; Sarcoma/surgery ; Thymus Neoplasms
    Language English
    Publishing date 2020-01-31
    Publishing country United States
    Document type Editorial ; Comment
    ZDB-ID 3104-5
    ISSN 1097-685X ; 0022-5223
    ISSN (online) 1097-685X
    ISSN 0022-5223
    DOI 10.1016/j.jtcvs.2020.01.033
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: CMR in the Era of COVID-19: Evaluation of Myocarditis in the Subacute Phase.

    Salerno, Michael / Kwong, Raymond Y

    JACC. Cardiovascular imaging

    2020  Volume 13, Issue 11, Page(s) 2340–2342

    MeSH term(s) Betacoronavirus ; COVID-19 ; Coronavirus Infections ; Humans ; Magnetic Resonance Imaging ; Myocarditis/diagnostic imaging ; Pandemics ; Pneumonia, Viral ; SARS-CoV-2
    Keywords covid19
    Language English
    Publishing date 2020-07-03
    Publishing country United States
    Document type Editorial ; Comment
    ZDB-ID 2491503-8
    ISSN 1876-7591 ; 1936-878X
    ISSN (online) 1876-7591
    ISSN 1936-878X
    DOI 10.1016/j.jcmg.2020.06.013
    Database MEDical Literature Analysis and Retrieval System OnLINE

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