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Yonsei Medical Journal|January 18, 2022
Detection and Weak Segmentation of Masses in Gray-Scale Breast Mammogram Images Using Deep LearningYoung Jae Kim, Kwang Gi KimTaehan Yongsang Uihakhoe Chi|October 14, 2022
[Development of an Optimized Deep Learning Model for Medical Imaging]Young Jae Kim, Kwang Gi KimJournal of the Korean Society of Radiology|December 22, 2022
[Understanding and Application of Multi-Task Learning in Medical Artificial Intelligence]Young Jae Kim, Kwang Gi KimComputational and Mathematical Methods in Medicine|May 4, 2018
Automated Segmentation Methods of Drusen to Diagnose Age-Related Macular Degeneration Screening in Retinal ImagesYoung Jae Kim, Kwang Gi KimHealthcare Informatics Research|February 22, 2020
Web-Based Spine Segmentation Using Deep Learning in Computed Tomography ImagesYoung Jae Kim, Bilegt Ganbold, Kwang Gi KimJournal of Korean Medical Science|December 8, 2017
A Fast 3-Dimensional Magnetic Resonance Imaging Reconstruction for Surgical Planning of Uterine MyomectomySa Ra Lee, Young Jae Kim, Kwang Gi KimSensors (Basel, Switzerland)|May 20, 2022
Segmentation Performance Comparison Considering Regional Characteristics in Chest X-ray Using Deep LearningHyo Min Lee, Young Jae Kim, Kwang Gi KimBiomedical Engineering Letters|August 28, 2020
Bone age estimation using deep learning and hand X-ray imagesJang Hyung Lee, Young Jae Kim, Kwang Gi KimJournal of Imaging Informatics in Medicine|January 21, 2026
Hemorrhage Segmentation in Fundus Images Using the U-Net 3+ Model: Performance Comparison Across Retinal RegionsYeong Hun Kang, Young Jae Kim, Kwang Gi KimJournal of Imaging Informatics in Medicine|February 5, 2025
Comparative Analysis of U-Net and U-Net3 + for Retinal Exudate Segmentation: Performance Evaluation Across RegionsYeong Hun Kang, Young Jae Kim, Kwang Gi KimPageof 53