Jihye Yun

发表

Deep Learning Applications in Chest Radiography and Computed Tomography: Current State of the Art

Sang Min Lee, E. V. van Beek, J. Gee, 2019, Journal of thoracic imaging.

Federated learning enables big data for rare cancer boundary detection

Bjoern H Menze, Amber L. Simpson, James F. Gimpel, 2022, Nature Communications.

Oropharyngeal squamous cell carcinoma: radiomic machine-learning classifiers from multiparametric MR images for determination of HPV infection status

Jeong Hyun Lee, Namkug Kim, Y. Choi, 2020, Scientific Reports.

3D Cascaded U-Net with a Squeeze-and-Exicitation Block for Semantic Segmentation on Kidney and Renal Cell Carcinoma in Abdonimal Volumetric CT

Namkug Kim, Jihye Yun, S. Ham, 2019, Submissions to the 2019 Kidney Tumor Segmentation Challenge: KiTS19.

Development of machine learning-based clinical decision support system for hepatocellular carcinoma

Namkug Kim, H. Lee, Y. Chung, 2020, Scientific Reports.

Artificial Intelligence in Lung Imaging

Sang Min Lee, J. Seo, Namkug Kim, 2022, Seminars in Respiratory and Critical Care Medicine.

Development and Validation of a Model Using Radiomics Features from an Apparent Diffusion Coefficient Map to Diagnose Local Tumor Recurrence in Patients Treated for Head and Neck Squamous Cell Carcinoma

Jeong Hyun Lee, Namkug Kim, Y. Choi, 2022, Korean journal of radiology.

Federated learning enables big data for rare cancer boundary detection

Bjoern H Menze, Amber L. Simpson, James F. Gimpel, 2022, Nature Communications.

Interstitial lung abnormalities (ILA) on routine chest CT: Comparison of radiologists' visual evaluation and automated quantification.

Sang Min Lee, J. Seo, Namkug Kim, 2022, European journal of radiology.

Multi-domain CT translation by a routable translation network

Jihye Yun, Joon Beom Seo, Hye Jeon Hwang, 2022, Physics in medicine and biology.

Machine learning approach for differentiating cytomegalovirus esophagitis from herpes simplex virus esophagitis

Namkug Kim, D. Kim, Jihye Yun, 2021, Scientific Reports.

Diffusion and perfusion MRI radiomics obtained from deep learning segmentation provides reproducible and comparable diagnostic model to human in post-treatment glioblastoma

Hyunna Lee, Namkug Kim, S. Park, 2020, European Radiology.

Radiomic features and multilayer perceptron network classifier: a robust MRI classification strategy for distinguishing glioblastoma from primary central nervous system lymphoma

Hyunna Lee, Namkug Kim, H. Kim, 2019, Scientific Reports.

Deep Learning-based Approach to Predict Pulmonary Function at Chest CT.

Sang Min Lee, J. Seo, Namkug Kim, 2023, Radiology.

Deep radiomics-based survival prediction in patients with chronic obstructive pulmonary disease

Jae Seung Lee, J. Seo, Namkug Kim, 2021, Scientific Reports.