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Hyunkwang Lee

Showing results (1-10 of 10) with videos related to

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Journal of Digital Imaging|October 7, 2017
A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip DetectionHyunkwang Lee, Mohammad Mansouri, Shahein Tajmir, et al.
Scientific Reports|October 31, 2019
Machine Friendly Machine Learning: Interpretation of Computed Tomography Without Image ReconstructionHyunkwang Lee, Chao Huang, Sehyo Yune, et al.
Journal of Digital Imaging|November 28, 2018
Beyond Human Perception: Sexual Dimorphism in Hand and Wrist Radiographs Is Discernible by a Deep Learning ModelSehyo Yune, Hyunkwang Lee, Myeongchan Kim, et al.
Radiology. Artificial Intelligence|May 3, 2021
Urinary Stone Detection on CT Images Using Deep Convolutional Neural Networks: Evaluation of Model Performance and GeneralizationAnushri Parakh, Hyunkwang Lee, Jeong Hyun Lee, et al.
Journal of Digital Imaging|June 28, 2017
Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric AnalysisHyunkwang Lee, Fabian M Troschel, Shahein Tajmir, et al.
Journal of Digital Imaging|March 10, 2017
Fully Automated Deep Learning System for Bone Age AssessmentHyunkwang Lee, Shahein Tajmir, Jenny Lee, et al.
Radiology. Artificial Intelligence|February 7, 2024
Impact of a Categorical AI System for Digital Breast Tomosynthesis on Breast Cancer Interpretation by Both General Radiologists and Breast Imaging SpecialistsJiye G Kim, Bryan Haslam, Abdul Rahman Diab, et al.
Skeletal Radiology|August 3, 2018
Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variabilityShahein H Tajmir, Hyunkwang Lee, Randheer Shailam, et al.
Journal of Medical Imaging (Bellingham, Wash.)|May 28, 2026
OMAMA-DB: the Oregon-Massachusetts Mammography DatabaseAvanith Kanamarlapudi, Ryan Zurrin, Edward Gaibor, et al.
Nature Biomedical Engineering|April 6, 2019
An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasetsHyunkwang Lee, Sehyo Yune, Mohammad Mansouri, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
Journal of Digital Imaging|October 7, 2017
A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip DetectionHyunkwang Lee, Mohammad Mansouri, Shahein Tajmir, et al.
Scientific Reports|October 31, 2019
Machine Friendly Machine Learning: Interpretation of Computed Tomography Without Image ReconstructionHyunkwang Lee, Chao Huang, Sehyo Yune, et al.
Journal of Digital Imaging|November 28, 2018
Beyond Human Perception: Sexual Dimorphism in Hand and Wrist Radiographs Is Discernible by a Deep Learning ModelSehyo Yune, Hyunkwang Lee, Myeongchan Kim, et al.
Radiology. Artificial Intelligence|May 3, 2021
Urinary Stone Detection on CT Images Using Deep Convolutional Neural Networks: Evaluation of Model Performance and GeneralizationAnushri Parakh, Hyunkwang Lee, Jeong Hyun Lee, et al.
Journal of Digital Imaging|June 28, 2017
Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric AnalysisHyunkwang Lee, Fabian M Troschel, Shahein Tajmir, et al.
Journal of Digital Imaging|March 10, 2017
Fully Automated Deep Learning System for Bone Age AssessmentHyunkwang Lee, Shahein Tajmir, Jenny Lee, et al.
Radiology. Artificial Intelligence|February 7, 2024
Impact of a Categorical AI System for Digital Breast Tomosynthesis on Breast Cancer Interpretation by Both General Radiologists and Breast Imaging SpecialistsJiye G Kim, Bryan Haslam, Abdul Rahman Diab, et al.
Skeletal Radiology|August 3, 2018
Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variabilityShahein H Tajmir, Hyunkwang Lee, Randheer Shailam, et al.
Journal of Medical Imaging (Bellingham, Wash.)|May 28, 2026
OMAMA-DB: the Oregon-Massachusetts Mammography DatabaseAvanith Kanamarlapudi, Ryan Zurrin, Edward Gaibor, et al.
Nature Biomedical Engineering|April 6, 2019
An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasetsHyunkwang Lee, Sehyo Yune, Mohammad Mansouri, et al.
Pageof 1