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Synho Do

Showing results (11-20 of 74) with videos related to

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IEEE Transactions on Medical Imaging|August 10, 2006
Segmentation methodology for automated classification and differentiation of soft tissues in multiband images of high-resolution ultrasonic transmission tomographyJeong-Won Jeong, Dae C Shin, Synho Do, et al.
Research Square|December 8, 2025
Generative AI-Enhanced Microcalcification Detection in Full-Field Digital Mammography: Reducing False Positives with High SensitivityKyungsu Kim, Manisha Bahl, Adham Mahmoud Alkhadrawi, et al.
Briefings in Bioinformatics|December 15, 2025
Response to 'Methodological and statistical concerns in MINERVA microbiome-disease knowledge graph' by Salvatore ChirumboloSaul Langarica, Young-Tak Kim, Adham Alkhadrawi, et al.
Briefings in Bioinformatics|September 23, 2025
MINERVA-microbiome network research and visualization atlas: a scalable knowledge graph for mapping microbiome-disease associationsSaul Langarica, Young-Tak Kim, Adham Alkhadrawi, et al.
Radiology|July 29, 2025
AI to Reduce the Interval Cancer Rate of Screening Digital Breast TomosynthesisManisha Bahl, Saul Langarica, Leslie R Lamb, 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.
Computational and Mathematical Methods in Medicine|October 20, 2012
Automated quantification of pneumothorax in CTSynho Do, Kristen Salvaggio, Supriya Gupta, 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.
AI in Precision Oncology|April 4, 2025
Artificial Intelligence (AI)-Based Computer-Assisted Detection and Diagnosis for Mammography: An Evidence-Based Review of Food and Drug Administration (FDA)-Cleared Tools for Screening Digital Breast Tomosynthesis (DBT)Leslie R Lamb, Constance D Lehman, Synho Do, et al.
Journal of the American College of Radiology : JACR|March 18, 2018
Interventional Radiology Training Using a Dynamic Medical Immersive Training Environment (DynaMITE)Colin J McCarthy, Alvin Y C Yu, Synho Do, et al.
Pageof 8

Showing results (11-20 of 74) with videos related to

Sort By:
Pageof 8
IEEE Transactions on Medical Imaging|August 10, 2006
Segmentation methodology for automated classification and differentiation of soft tissues in multiband images of high-resolution ultrasonic transmission tomographyJeong-Won Jeong, Dae C Shin, Synho Do, et al.
Research Square|December 8, 2025
Generative AI-Enhanced Microcalcification Detection in Full-Field Digital Mammography: Reducing False Positives with High SensitivityKyungsu Kim, Manisha Bahl, Adham Mahmoud Alkhadrawi, et al.
Briefings in Bioinformatics|December 15, 2025
Response to 'Methodological and statistical concerns in MINERVA microbiome-disease knowledge graph' by Salvatore ChirumboloSaul Langarica, Young-Tak Kim, Adham Alkhadrawi, et al.
Briefings in Bioinformatics|September 23, 2025
MINERVA-microbiome network research and visualization atlas: a scalable knowledge graph for mapping microbiome-disease associationsSaul Langarica, Young-Tak Kim, Adham Alkhadrawi, et al.
Radiology|July 29, 2025
AI to Reduce the Interval Cancer Rate of Screening Digital Breast TomosynthesisManisha Bahl, Saul Langarica, Leslie R Lamb, 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.
Computational and Mathematical Methods in Medicine|October 20, 2012
Automated quantification of pneumothorax in CTSynho Do, Kristen Salvaggio, Supriya Gupta, 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.
AI in Precision Oncology|April 4, 2025
Artificial Intelligence (AI)-Based Computer-Assisted Detection and Diagnosis for Mammography: An Evidence-Based Review of Food and Drug Administration (FDA)-Cleared Tools for Screening Digital Breast Tomosynthesis (DBT)Leslie R Lamb, Constance D Lehman, Synho Do, et al.
Journal of the American College of Radiology : JACR|March 18, 2018
Interventional Radiology Training Using a Dynamic Medical Immersive Training Environment (DynaMITE)Colin J McCarthy, Alvin Y C Yu, Synho Do, et al.
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