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F Laine

Showing results (151-160 of 160) with videos related to

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Magnetic Resonance Imaging|July 1, 2022
Quantification of lung ventilation defects on hyperpolarized MRI: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD studyXuzhe Zhang, Elsa D Angelini, Fateme S Haghpanah, et al.
Nature Methods|November 13, 2023
High-fidelity 3D live-cell nanoscopy through data-driven enhanced super-resolution radial fluctuationRomain F Laine, Hannah S Heil, Simao Coelho, et al.
European Heart Journal. Imaging Methods and Practice|July 24, 2024
Absence of long-term structural and functional cardiac abnormalities on multimodality imaging in a multi-ethnic group of COVID-19 survivors from the early stage of the pandemicLorenzo R Sewanan, Marco R Di Tullio, Andrew F Laine, et al.
Nature Communications|April 16, 2021
Democratising deep learning for microscopy with ZeroCostDL4MicLucas von Chamier, Romain F Laine, Johanna Jukkala, et al.
Scientific Reports|November 1, 2019
OptiJ: Open-source optical projection tomography of large organ samplesPedro P Vallejo Ramirez, Joseph Zammit, Oliver Vanderpoorten, et al.
Thorax|January 23, 2023
<i>MUC5B</i>, telomere length and longitudinal quantitative interstitial lung changes: the MESA Lung StudyJohn S Kim, Ani W Manichaikul, Eric A Hoffman, et al.
Eclinicalmedicine|June 7, 2024
Artificial intelligence for cardiovascular disease risk assessment in personalised framework: a scoping reviewManasvi Singh, Ashish Kumar, Narendra N Khanna, et al.
Frontiers in Cell and Developmental Biology|April 8, 2021
Comparative Studies in the A30P and A53T α-Synuclein <i>C. elegans</i> Strains to Investigate the Molecular Origins of Parkinson's DiseaseMichele Perni, Annemieke van der Goot, Ryan Limbocker, et al.
Science (New York, N.Y.)|November 16, 2016
De novo design of a biologically active amyloidRodrigo Gallardo, Meine Ramakers, Frederik De Smet, et al.
Thorax|June 2, 2023
Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scansElsa D Angelini, Jie Yang, Pallavi P Balte, et al.
Pageof 16

Showing results (151-160 of 160) with videos related to

Sort By:
Pageof 16
You have reached the last page of results.This site can display upto 160 results.
Magnetic Resonance Imaging|July 1, 2022
Quantification of lung ventilation defects on hyperpolarized MRI: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD studyXuzhe Zhang, Elsa D Angelini, Fateme S Haghpanah, et al.
Nature Methods|November 13, 2023
High-fidelity 3D live-cell nanoscopy through data-driven enhanced super-resolution radial fluctuationRomain F Laine, Hannah S Heil, Simao Coelho, et al.
European Heart Journal. Imaging Methods and Practice|July 24, 2024
Absence of long-term structural and functional cardiac abnormalities on multimodality imaging in a multi-ethnic group of COVID-19 survivors from the early stage of the pandemicLorenzo R Sewanan, Marco R Di Tullio, Andrew F Laine, et al.
Nature Communications|April 16, 2021
Democratising deep learning for microscopy with ZeroCostDL4MicLucas von Chamier, Romain F Laine, Johanna Jukkala, et al.
Scientific Reports|November 1, 2019
OptiJ: Open-source optical projection tomography of large organ samplesPedro P Vallejo Ramirez, Joseph Zammit, Oliver Vanderpoorten, et al.
Thorax|January 23, 2023
<i>MUC5B</i>, telomere length and longitudinal quantitative interstitial lung changes: the MESA Lung StudyJohn S Kim, Ani W Manichaikul, Eric A Hoffman, et al.
Eclinicalmedicine|June 7, 2024
Artificial intelligence for cardiovascular disease risk assessment in personalised framework: a scoping reviewManasvi Singh, Ashish Kumar, Narendra N Khanna, et al.
Frontiers in Cell and Developmental Biology|April 8, 2021
Comparative Studies in the A30P and A53T α-Synuclein <i>C. elegans</i> Strains to Investigate the Molecular Origins of Parkinson's DiseaseMichele Perni, Annemieke van der Goot, Ryan Limbocker, et al.
Science (New York, N.Y.)|November 16, 2016
De novo design of a biologically active amyloidRodrigo Gallardo, Meine Ramakers, Frederik De Smet, et al.
Thorax|June 2, 2023
Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scansElsa D Angelini, Jie Yang, Pallavi P Balte, et al.
Pageof 16