Deep Learning for Diagnosis of Paranasal Sinusitis Using Multi-View Radiographs
Yejin Jeon(Seoul National University Bundang Hospital), Jae Hyoung Kim(Seoul National University), Jeong‐Whun Kim(University of Pittsburgh), Kyeorye Lee(Seoul National University Bundang Hospital), Youngjune Kim(Seoul National University), Byung Se Choi(Seoul National University), Roh‐Eul Yoo(Seoul National University), Leonard Sunwoo(Seoul National University), Kyong Joon Lee(Seoul National University), Sung Hyun Baik(Seoul National University Bundang Hospital), Yun Jung Bae(Seoul National University), Se Jin Cho(Seoul National University Bundang Hospital), Dong Yul Oh(Seoul National University Bundang Hospital), Dongjun Choi(Seoul National University Bundang Hospital), Cheolkyu Jung(Seoul National University)
Cited by 43
Related Papers
2021 Korean Thyroid Imaging Reporting and Data System and Imaging-Based Management of Thyroid Nodules: Korean Society of Thyroid Radiology Consensus Statement and Recommendations
|Korean Journal of Radiology|2021|277
Incorporating diffusion- and perfusion-weighted MRI into a radiomics model improves diagnostic performance for pseudoprogression in glioblastoma patients
|Neuro-Oncology|2018|225
Deep Learning in Diagnosis of Maxillary Sinusitis Using Conventional Radiography
|Investigative Radiology|2018|108
Contrast-enhanced MRI T1 Mapping for Quantitative Evaluation of Putative Dynamic Glymphatic Activity in the Human Brain in Sleep-Wake States
|Radiology|2021|94
Radiomics prognostication model in glioblastoma using diffusion- and perfusion-weighted MRI
|Scientific Reports|2020|77