C. Ahn

发表

A Challenge for Emphysema Quantification Using a Deep Learning Algorithm With Low-dose Chest Computed Tomography

J. Goo, Hyungjin Kim, H. Lee, 2022, Journal of thoracic imaging.

Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique

Yeon Jin Cho, Jong Hyo Kim, W. Kim, 2020, European Radiology.

Incremental Image Noise Reduction in Coronary CT Angiography Using a Deep Learning-Based Technique with Iterative Reconstruction

Jong Hyo Kim, J. Hong, Whal Lee, 2020, Korean journal of radiology.

Fully automated image quality evaluation on patient CT: Multi-vendor and multi-reconstruction study

Sihwan Kim, C. Ahn, M. Chun, 2022, PloS one.

Deep learning–based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis

Jong Hyo Kim, J. Lee, J. S. Bae, 2022, European Radiology.

Image quality in liver CT: low-dose deep learning vs standard-dose model-based iterative reconstructions

Jong Hyo Kim, J. Lee, I. Joo, 2021, European Radiology.

Dose reduction potential of vendor-agnostic deep learning model in comparison with deep learning–based image reconstruction algorithm on CT: a phantom study

Hae Young Kim, Jong Hyo Kim, Won Chang, 2021, European Radiology.

A deep learning-enabled iterative reconstruction of ultra-low-dose CT: use of synthetic sinogram-based noise simulation technique

Byungjun Park, Changyong Heo, Zepa Yang, 2018, Medical Imaging.

A novel deep learning-based approach to high accuracy breast density estimation in digital mammography

Jong Hyo Kim, Changyong Heo, Chul Kyun Ahn, 2017, Medical Imaging.

Performance of 1-mm non-gated low-dose chest computed tomography using deep learning-based noise reduction for coronary artery calcium scoring

Hyewon Choi, Whal Lee, C. Ahn, 2022, European Radiology.

Deep learning-based reconstruction of virtual monoenergetic images of kVp-switching dual energy CT for evaluation of hypervascular liver lesions: Comparison with standard reconstruction technique.

Jong Hyo Kim, J. Lee, I. Joo, 2022, European journal of radiology.

Low dose of contrast agent and low radiation liver computed tomography with deep-learning-based contrast boosting model in participants at high-risk for hepatocellular carcinoma: prospective, randomized, double-blind study

Jeong Min Lee, J. S. Bae, J. Yoon, 2023, European Radiology.

Deep Learning Algorithm for Simultaneous Noise Reduction and Edge Sharpening in Low-Dose CT Images: A Pilot Study Using Lumbar Spine CT

Jong Hyo Kim, H. Chae, J. Choi, 2021, Korean Journal of Radiology.

Image quality of ultralow-dose chest CT using deep learning techniques: potential superiority of vendor-agnostic post-processing over vendor-specific techniques

J. Nam, J. Goo, Jong Hyo Kim, 2021, European Radiology.

75% radiation dose reduction using deep learning reconstruction on low-dose chest CT

J. Nam, J. Hong, C. Ahn, 2023, BMC Medical Imaging.

AntiHalluciNet: A Potential Auditing Tool of the Behavior of Deep Learning Denoising Models in Low-Dose Computed Tomography

C. Ahn, Jong Hyo Kim, 2023, Diagnostics.