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NMR in Biomedicine
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March 25, 2024
A review of self-supervised, generative, and few-shot deep learning methods for data-limited magnetic resonance imaging segmentation
Zelong Liu, Komal Kainth, Alexander Zhou, et al.
European Radiology
|
November 17, 2020
Fully automated prediction of liver fibrosis using deep learning analysis of gadoxetic acid-enhanced MRI
Stefanie J Hectors, Paul Kennedy, Kuang-Han Huang, et al.
Scientific Reports
|
May 10, 2023
Multimodal fusion models for pulmonary embolism mortality prediction
Noa Cahan, Eyal Klang, Edith M Marom, et al.
ACS Sensors
|
March 7, 2018
Electrostatic Selectivity of Volatile Organic Compounds Using Electrostatically Formed Nanowire Sensor
Niharendu Mahapatra, Avi Ben-Cohen, Yonathan Vaknin, et al.
IEEE Journal of Biomedical and Health Informatics
|
September 16, 2015
Improved Patch-Based Automated Liver Lesion Classification by Separate Analysis of the Interior and Boundary Regions
Idit Diamant, Assaf Hoogi, Christopher F Beaulieu, et al.
Bioengineering (Basel, Switzerland)
|
December 23, 2023
Discovery Viewer (DV): Web-Based Medical AI Model Development Platform and Deployment Hub
Valentin Fauveau, Sean Sun, Zelong Liu, et al.
Academic Radiology
|
August 6, 2017
CT Image-based Decision Support System for Categorization of Liver Metastases Into Primary Cancer Sites: Initial Results
Avi Ben-Cohen, Eyal Klang, Idit Diamant, et al.
Studies in Health Technology and Informatics
|
September 16, 2010
AALIM: a cardiac clinical decision support system powered by advanced multi-modal analytics
Arnon Amir, David Beymer, Julia Grace, et al.
NMR in Biomedicine
|
April 6, 2023
Estimation of subvoxel fat infiltration in neurodegenerative muscle disorders using quantitative multi-T<sub>2</sub> analysis
Jannette Nassar, Amira Trabelsi, Rula Amer, et al.
Proceedings of the IEEE. Institute of Electrical and Electronics Engineers
|
October 3, 2023
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
S Kevin Zhou, Hayit Greenspan, Christos Davatzikos, et al.
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Showing results (51-60 of 78) with videos related to
Sort By:
Page
of 8
NMR in Biomedicine
|
March 25, 2024
A review of self-supervised, generative, and few-shot deep learning methods for data-limited magnetic resonance imaging segmentation
Zelong Liu, Komal Kainth, Alexander Zhou, et al.
European Radiology
|
November 17, 2020
Fully automated prediction of liver fibrosis using deep learning analysis of gadoxetic acid-enhanced MRI
Stefanie J Hectors, Paul Kennedy, Kuang-Han Huang, et al.
Scientific Reports
|
May 10, 2023
Multimodal fusion models for pulmonary embolism mortality prediction
Noa Cahan, Eyal Klang, Edith M Marom, et al.
ACS Sensors
|
March 7, 2018
Electrostatic Selectivity of Volatile Organic Compounds Using Electrostatically Formed Nanowire Sensor
Niharendu Mahapatra, Avi Ben-Cohen, Yonathan Vaknin, et al.
IEEE Journal of Biomedical and Health Informatics
|
September 16, 2015
Improved Patch-Based Automated Liver Lesion Classification by Separate Analysis of the Interior and Boundary Regions
Idit Diamant, Assaf Hoogi, Christopher F Beaulieu, et al.
Bioengineering (Basel, Switzerland)
|
December 23, 2023
Discovery Viewer (DV): Web-Based Medical AI Model Development Platform and Deployment Hub
Valentin Fauveau, Sean Sun, Zelong Liu, et al.
Academic Radiology
|
August 6, 2017
CT Image-based Decision Support System for Categorization of Liver Metastases Into Primary Cancer Sites: Initial Results
Avi Ben-Cohen, Eyal Klang, Idit Diamant, et al.
Studies in Health Technology and Informatics
|
September 16, 2010
AALIM: a cardiac clinical decision support system powered by advanced multi-modal analytics
Arnon Amir, David Beymer, Julia Grace, et al.
NMR in Biomedicine
|
April 6, 2023
Estimation of subvoxel fat infiltration in neurodegenerative muscle disorders using quantitative multi-T<sub>2</sub> analysis
Jannette Nassar, Amira Trabelsi, Rula Amer, et al.
Proceedings of the IEEE. Institute of Electrical and Electronics Engineers
|
October 3, 2023
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
S Kevin Zhou, Hayit Greenspan, Christos Davatzikos, et al.
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of 8