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Journal of Digital Imaging
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October 7, 2017
A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip Detection
Hyunkwang Lee, Mohammad Mansouri, Shahein Tajmir, et al.
Scientific Reports
|
October 31, 2019
Machine Friendly Machine Learning: Interpretation of Computed Tomography Without Image Reconstruction
Hyunkwang 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 Model
Sehyo 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 Generalization
Anushri 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 Analysis
Hyunkwang Lee, Fabian M Troschel, Shahein Tajmir, et al.
Journal of Digital Imaging
|
March 10, 2017
Fully Automated Deep Learning System for Bone Age Assessment
Hyunkwang 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 Specialists
Jiye 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 variability
Shahein H Tajmir, Hyunkwang Lee, Randheer Shailam, et al.
Journal of Medical Imaging (Bellingham, Wash.)
|
May 28, 2026
OMAMA-DB: the Oregon-Massachusetts Mammography Database
Avanith 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 datasets
Hyunkwang Lee, Sehyo Yune, Mohammad Mansouri, et al.
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of 1
Search research articles
Search
Showing results (1-10 of 10) with videos related to
Sort By:
Page
of 1
Journal of Digital Imaging
|
October 7, 2017
A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip Detection
Hyunkwang Lee, Mohammad Mansouri, Shahein Tajmir, et al.
Scientific Reports
|
October 31, 2019
Machine Friendly Machine Learning: Interpretation of Computed Tomography Without Image Reconstruction
Hyunkwang 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 Model
Sehyo 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 Generalization
Anushri 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 Analysis
Hyunkwang Lee, Fabian M Troschel, Shahein Tajmir, et al.
Journal of Digital Imaging
|
March 10, 2017
Fully Automated Deep Learning System for Bone Age Assessment
Hyunkwang 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 Specialists
Jiye 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 variability
Shahein H Tajmir, Hyunkwang Lee, Randheer Shailam, et al.
Journal of Medical Imaging (Bellingham, Wash.)
|
May 28, 2026
OMAMA-DB: the Oregon-Massachusetts Mammography Database
Avanith 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 datasets
Hyunkwang Lee, Sehyo Yune, Mohammad Mansouri, et al.
Page
of 1