Ahn C - Search Results

1

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

Choi H, Chang W, Kim JH, Ahn C, Lee H, Kim HY, Cho J, Lee YJ, Kim YH. Choi H, et al. Among authors: ahn c. Eur Radiol. 2022 Feb;32(2):1247-1255. doi: 10.1007/s00330-021-08199-9. Epub 2021 Aug 14. Eur Radiol. 2022. PMID: 34390372 Free PMC article.

2

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

Hong JH, Park EA, Lee W, Ahn C, Kim JH. Hong JH, et al. Among authors: ahn c. Korean J Radiol. 2020 Oct;21(10):1165-1177. doi: 10.3348/kjr.2020.0020. Epub 2020 Jul 17. Korean J Radiol. 2020. PMID: 32729262 Free PMC article.

3

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

Lee S, Choi YH, Cho YJ, Lee SB, Cheon JE, Kim WS, Ahn CK, Kim JH. Lee S, et al. Eur Radiol. 2021 Apr;31(4):2218-2226. doi: 10.1007/s00330-020-07349-9. Epub 2020 Oct 8. Eur Radiol. 2021. PMID: 33030573

4

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

Nam JG, Ahn C, Choi H, Hong W, Park J, Kim JH, Goo JM. Nam JG, et al. Among authors: ahn c. Eur Radiol. 2021 Jul;31(7):5139-5147. doi: 10.1007/s00330-020-07537-7. Epub 2021 Jan 7. Eur Radiol. 2021. PMID: 33415436

5

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

Nam JG, Ahn C, Choi H, Hong W, Park J, Kim JH, Goo JM. Nam JG, et al. Among authors: ahn c. Eur Radiol. 2021 Aug;31(8):6410. doi: 10.1007/s00330-021-07733-z. Eur Radiol. 2021. PMID: 33590320 No abstract available.

6

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

Yeoh H, Hong SH, Ahn C, Choi JY, Chae HD, Yoo HJ, Kim JH. Yeoh H, et al. Among authors: ahn c. Korean J Radiol. 2021 Nov;22(11):1850-1857. doi: 10.3348/kjr.2021.0140. Epub 2021 Aug 19. Korean J Radiol. 2021. PMID: 34431248 Free PMC article.

7

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

Park S, Yoon JH, Joo I, Yu MH, Kim JH, Park J, Kim SW, Han S, Ahn C, Kim JH, Lee JM. Park S, et al. Among authors: ahn c. Eur Radiol. 2022 May;32(5):2865-2874. doi: 10.1007/s00330-021-08380-0. Epub 2021 Nov 25. Eur Radiol. 2022. PMID: 34821967

8

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

Lee T, Lee JM, Yoon JH, Joo I, Bae JS, Yoo J, Kim JH, Ahn C, Kim JH. Lee T, et al. Among authors: ahn c. Eur Radiol. 2022 Sep;32(9):6407-6417. doi: 10.1007/s00330-022-08728-0. Epub 2022 Apr 5. Eur Radiol. 2022. PMID: 35380228

9

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.

Seo JY, Joo I, Yoon JH, Kang HJ, Kim S, Kim JH, Ahn C, Lee JM. Seo JY, et al. Among authors: ahn c. Eur J Radiol. 2022 Sep;154:110390. doi: 10.1016/j.ejrad.2022.110390. Epub 2022 Jun 15. Eur J Radiol. 2022. PMID: 35724579

10

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

Chun M, Choi JH, Kim S, Ahn C, Kim JH. Chun M, et al. Among authors: ahn c. PLoS One. 2022 Jul 20;17(7):e0271724. doi: 10.1371/journal.pone.0271724. eCollection 2022. PLoS One. 2022. PMID: 35857804 Free PMC article.

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