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Yongwon Cho

Showing results (51-60 of 61) with videos related to

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BMC Medical Informatics and Decision Making|June 3, 2024
Correction: Deep learning model for differentiating nasal cavity masses based on nasal endoscopy imagesJunhu Tai, Munsoo Han, Bo Yoon Choi, et al.
European Radiology|September 16, 2022
Identifying fragile calcifications of the aortic valve in transcatheter aortic valve replacement: iodine concentration of aortic valvular calcification by spectral CTSoojung Park, Yongwon Cho, Yu-Whan Oh, et al.
Computer Methods and Programs in Biomedicine|October 19, 2019
Fully automated 3D segmentation and separation of multiple cervical vertebrae in CT images using a 2D convolutional neural networkHyun-Jin Bae, Heejung Hyun, Younghwa Byeon, et al.
BMC Medical Informatics and Decision Making|May 29, 2024
Deep learning model for differentiating nasal cavity masses based on nasal endoscopy imagesJunhu Tai, Munsoo Han, Bo Yoon Choi, et al.
Journal of Korean Medical Science|September 19, 2023
Aortic Annulus Detection Based on Deep Learning for Transcatheter Aortic Valve Replacement Using Cardiac Computed TomographyYongwon Cho, Soojung Park, Sung Ho Hwang, et al.
Abdominal Radiology (New York)|September 21, 2022
Hepatocellular carcinoma pathologic grade prediction using radiomics and machine learning models of gadoxetic acid-enhanced MRI: a two-center studyYeo Eun Han, Yongwon Cho, Min Ju Kim, et al.
Scientific Reports|December 12, 2019
Short-term Reproducibility of Pulmonary Nodule and Mass Detection in Chest Radiographs: Comparison among Radiologists and Four Different Computer-Aided Detections with Convolutional Neural NetYoung-Gon Kim, Yongwon Cho, Chen-Jiang Wu, et al.
Abdominal Radiology (New York)|October 26, 2023
Development and validation of CT‑based radiomics model of PET-negative residual CT masses: a potential biomarker for predicting relapse‑free survival in non-Hodgkin lymphoma patients showing complete metabolic responseSeung Ha Cha, Ka-Won Kang, Na Yeon Han, et al.
Journal of Computer Assisted Tomography|April 28, 2022
Diagnostic Feasibility of Magnetic Resonance Elastography Radiomics Analysis for the Assessment of Hepatic Fibrosis in Patients With Nonalcoholic Fatty Liver DiseaseKi Choon Sim, Min Ju Kim, Yongwon Cho, et al.
Journal of Korean Medical Science|December 20, 2022
Radiomics Analysis of Magnetic Resonance Proton Density Fat Fraction for the Diagnosis of Hepatic Steatosis in Patients With Suspected Non-Alcoholic Fatty Liver DiseaseKi Choon Sim, Min Ju Kim, Yongwon Cho, et al.
Pageof 7

Showing results (51-60 of 61) with videos related to

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Pageof 7
BMC Medical Informatics and Decision Making|June 3, 2024
Correction: Deep learning model for differentiating nasal cavity masses based on nasal endoscopy imagesJunhu Tai, Munsoo Han, Bo Yoon Choi, et al.
European Radiology|September 16, 2022
Identifying fragile calcifications of the aortic valve in transcatheter aortic valve replacement: iodine concentration of aortic valvular calcification by spectral CTSoojung Park, Yongwon Cho, Yu-Whan Oh, et al.
Computer Methods and Programs in Biomedicine|October 19, 2019
Fully automated 3D segmentation and separation of multiple cervical vertebrae in CT images using a 2D convolutional neural networkHyun-Jin Bae, Heejung Hyun, Younghwa Byeon, et al.
BMC Medical Informatics and Decision Making|May 29, 2024
Deep learning model for differentiating nasal cavity masses based on nasal endoscopy imagesJunhu Tai, Munsoo Han, Bo Yoon Choi, et al.
Journal of Korean Medical Science|September 19, 2023
Aortic Annulus Detection Based on Deep Learning for Transcatheter Aortic Valve Replacement Using Cardiac Computed TomographyYongwon Cho, Soojung Park, Sung Ho Hwang, et al.
Abdominal Radiology (New York)|September 21, 2022
Hepatocellular carcinoma pathologic grade prediction using radiomics and machine learning models of gadoxetic acid-enhanced MRI: a two-center studyYeo Eun Han, Yongwon Cho, Min Ju Kim, et al.
Scientific Reports|December 12, 2019
Short-term Reproducibility of Pulmonary Nodule and Mass Detection in Chest Radiographs: Comparison among Radiologists and Four Different Computer-Aided Detections with Convolutional Neural NetYoung-Gon Kim, Yongwon Cho, Chen-Jiang Wu, et al.
Abdominal Radiology (New York)|October 26, 2023
Development and validation of CT‑based radiomics model of PET-negative residual CT masses: a potential biomarker for predicting relapse‑free survival in non-Hodgkin lymphoma patients showing complete metabolic responseSeung Ha Cha, Ka-Won Kang, Na Yeon Han, et al.
Journal of Computer Assisted Tomography|April 28, 2022
Diagnostic Feasibility of Magnetic Resonance Elastography Radiomics Analysis for the Assessment of Hepatic Fibrosis in Patients With Nonalcoholic Fatty Liver DiseaseKi Choon Sim, Min Ju Kim, Yongwon Cho, et al.
Journal of Korean Medical Science|December 20, 2022
Radiomics Analysis of Magnetic Resonance Proton Density Fat Fraction for the Diagnosis of Hepatic Steatosis in Patients With Suspected Non-Alcoholic Fatty Liver DiseaseKi Choon Sim, Min Ju Kim, Yongwon Cho, et al.
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