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Normal-resolution vs. super-resolution deep learning reconstruction for diagnosis of functionally significant coronary stenosis using cardiac CT.

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Bibliographic Details
Title: Normal-resolution vs. super-resolution deep learning reconstruction for diagnosis of functionally significant coronary stenosis using cardiac CT.
Authors: Tomizawa N; Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan. Electronic address: tomizawa-tky@umin.ac.jp., Fan R; Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan., Fujimoto S; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan., Nozaki YO; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan., Kawaguchi YO; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan., Takamura K; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan., Aikawa T; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan., Hiki M; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan., Takahashi N; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan., Okai I; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan., Okazaki S; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan., Minamino T; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan., Kamagata K; Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Source: Journal of cardiovascular computed tomography [J Cardiovasc Comput Tomogr] 2026 May-Jun; Vol. 20 (3), pp. 219-225. Date of Electronic Publication: 2026 Feb 18.
Publication Type: Journal Article; Comparative Study
Journal Info: Publisher: Elsevier Country of Publication: United States NLM ID: 101308347 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1876-861X (Electronic) Linking ISSN: 1876861X NLM ISO Abbreviation: J Cardiovasc Comput Tomogr Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1876-861X
DOI:10.1016/j.jcct.2026.01.016