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Radiology. Artificial Intelligence
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May 3, 2021
Urinary Stone Detection on CT Images Using Deep Convolutional Neural Networks: Evaluation of Model Performance and Generalization
Anushri Parakh, Hyunkwang Lee, Jeong Hyun Lee, et al.
Physics in Medicine and Biology
|
October 26, 2011
A decomposition-based CT reconstruction formulation for reducing blooming artifacts
Synho Do, W Clem Karl, Zhuangli Liang, et al.
Journal of the American College of Radiology : JACR
|
February 7, 2018
Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success
James H Thrall, Xiang Li, Quanzheng Li, et al.
Plos One
|
November 13, 2014
High fidelity system modeling for high quality image reconstruction in clinical CT
Synho Do, William Clem Karl, Sarabjeet Singh, et al.
IEEE Transactions on Medical Imaging
|
March 10, 2005
Soft tissue differentiation using multiband signatures of high resolution ultrasonic transmission tomography
Jeong-Won Jeong, Tae-Seong Kim, Dae C Shin, et al.
Academic Radiology
|
September 14, 2013
A novel analysis algorithm for potential quantitative assessment of myocardial computed tomography perfusion
Gary Liew, Nabeel Ali, Synho Do, et al.
Journal of Digital Imaging
|
June 28, 2017
Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis
Hyunkwang Lee, Fabian M Troschel, Shahein Tajmir, et al.
IEEE Transactions on Medical Imaging
|
April 10, 2010
A spatio-temporal deconvolution method to improve perfusion CT quantification
Lili He, Burkay Orten, Synho Do, et al.
OTA International : the Open Access Journal of Orthopaedic Trauma
|
December 28, 2023
A deep learning approach using an ensemble model to autocreate an image-based hip fracture registry
Jacobien H F Oosterhoff, Soomin Jeon, Bardiya Akhbari, et al.
NPJ Digital Medicine
|
February 20, 2026
Defining operational safety in clinical artificial intelligence systems
Young-Tak Kim, Hyunji Kim, Manisha Bahl, et al.
Page
of 8
Search research articles
Search
Showing results (21-30 of 74) with videos related to
Sort By:
Page
of 8
Radiology. Artificial Intelligence
|
May 3, 2021
Urinary Stone Detection on CT Images Using Deep Convolutional Neural Networks: Evaluation of Model Performance and Generalization
Anushri Parakh, Hyunkwang Lee, Jeong Hyun Lee, et al.
Physics in Medicine and Biology
|
October 26, 2011
A decomposition-based CT reconstruction formulation for reducing blooming artifacts
Synho Do, W Clem Karl, Zhuangli Liang, et al.
Journal of the American College of Radiology : JACR
|
February 7, 2018
Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success
James H Thrall, Xiang Li, Quanzheng Li, et al.
Plos One
|
November 13, 2014
High fidelity system modeling for high quality image reconstruction in clinical CT
Synho Do, William Clem Karl, Sarabjeet Singh, et al.
IEEE Transactions on Medical Imaging
|
March 10, 2005
Soft tissue differentiation using multiband signatures of high resolution ultrasonic transmission tomography
Jeong-Won Jeong, Tae-Seong Kim, Dae C Shin, et al.
Academic Radiology
|
September 14, 2013
A novel analysis algorithm for potential quantitative assessment of myocardial computed tomography perfusion
Gary Liew, Nabeel Ali, Synho Do, et al.
Journal of Digital Imaging
|
June 28, 2017
Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis
Hyunkwang Lee, Fabian M Troschel, Shahein Tajmir, et al.
IEEE Transactions on Medical Imaging
|
April 10, 2010
A spatio-temporal deconvolution method to improve perfusion CT quantification
Lili He, Burkay Orten, Synho Do, et al.
OTA International : the Open Access Journal of Orthopaedic Trauma
|
December 28, 2023
A deep learning approach using an ensemble model to autocreate an image-based hip fracture registry
Jacobien H F Oosterhoff, Soomin Jeon, Bardiya Akhbari, et al.
NPJ Digital Medicine
|
February 20, 2026
Defining operational safety in clinical artificial intelligence systems
Young-Tak Kim, Hyunji Kim, Manisha Bahl, et al.
Page
of 8