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Jong Hyo Kim

Showing results (1-10 of 70) with videos related to

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Diagnostics (Basel, Switzerland)|January 11, 2024
AntiHalluciNet: A Potential Auditing Tool of the Behavior of Deep Learning Denoising Models in Low-Dose Computed TomographyChulkyun Ahn, Jong Hyo Kim
European Journal of Radiology|May 24, 2011
History of PACS in AsiaKiyonari Inamura, Jong Hyo Kim
Medical Physics|January 7, 2014
Realistic simulation of reduced-dose CT with noise modeling and sinogram synthesis using DICOM CT imagesChang Won Kim, Jong Hyo Kim
Tomography (Ann Arbor, Mich.)|February 25, 2025
Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule CharacterizationDongok Kim, Chulkyun Ahn, Jong Hyo Kim
Medical Physics|July 4, 2018
Attenuation profile matching: An accurate and scan parameter-robust measurement method for small airway dimensions in low-dose CT scansZepa Yang, Hyeongmin Jin, Jong Hyo Kim
Physics in Medicine and Biology|June 12, 2019
Deep learning-enabled accurate normalization of reconstruction kernel effects on emphysema quantification in low-dose CTHyeongmin Jin, Changyong Heo, Jong Hyo Kim
Physics in Medicine and Biology|November 13, 2015
Automated measurement of CT noise in patient images with a novel structure coherence featureMinsoo Chun, Young Hun Choi, Jong Hyo Kim
Journal of Digital Imaging|July 10, 2002
Classification of malignant and benign tumors using boundary characteristics in breast ultrasonogramsKwang Gi Kim, Jong Hyo Kim, Byoung Goo Min
Journal of Glaucoma|January 25, 2019
Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar TransformationJinho Lee, Youngwoo Kim, Jong Hyo Kim, et al.
Journal of Imaging Informatics in Medicine|July 8, 2024
AI-assisted Segmentation Tool for Brain Tumor MR Image AnalysisMyungeun Lee, Jong Hyo Kim, Wookjin Choi, et al.
Pageof 7

Showing results (1-10 of 70) with videos related to

Sort By:
Pageof 7
Diagnostics (Basel, Switzerland)|January 11, 2024
AntiHalluciNet: A Potential Auditing Tool of the Behavior of Deep Learning Denoising Models in Low-Dose Computed TomographyChulkyun Ahn, Jong Hyo Kim
European Journal of Radiology|May 24, 2011
History of PACS in AsiaKiyonari Inamura, Jong Hyo Kim
Medical Physics|January 7, 2014
Realistic simulation of reduced-dose CT with noise modeling and sinogram synthesis using DICOM CT imagesChang Won Kim, Jong Hyo Kim
Tomography (Ann Arbor, Mich.)|February 25, 2025
Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule CharacterizationDongok Kim, Chulkyun Ahn, Jong Hyo Kim
Medical Physics|July 4, 2018
Attenuation profile matching: An accurate and scan parameter-robust measurement method for small airway dimensions in low-dose CT scansZepa Yang, Hyeongmin Jin, Jong Hyo Kim
Physics in Medicine and Biology|June 12, 2019
Deep learning-enabled accurate normalization of reconstruction kernel effects on emphysema quantification in low-dose CTHyeongmin Jin, Changyong Heo, Jong Hyo Kim
Physics in Medicine and Biology|November 13, 2015
Automated measurement of CT noise in patient images with a novel structure coherence featureMinsoo Chun, Young Hun Choi, Jong Hyo Kim
Journal of Digital Imaging|July 10, 2002
Classification of malignant and benign tumors using boundary characteristics in breast ultrasonogramsKwang Gi Kim, Jong Hyo Kim, Byoung Goo Min
Journal of Glaucoma|January 25, 2019
Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar TransformationJinho Lee, Youngwoo Kim, Jong Hyo Kim, et al.
Journal of Imaging Informatics in Medicine|July 8, 2024
AI-assisted Segmentation Tool for Brain Tumor MR Image AnalysisMyungeun Lee, Jong Hyo Kim, Wookjin Choi, et al.
Pageof 7