Health AI Central
Peer-Reviewed Publication
Diagnostics (Basel)2026;16(15)July 23, 2026Journal Article

AI-Driven Generation of Post-Contrast T1 and ECV Maps from Native T1 Map in Cardiac MRI.

Young Jung Yang1, Ga Hyeon Kim2, Yoon-Chul Kim2, Young Jin Kim3
1Phantomics, Inc., Magokseoro 152, Gangseo-gu, Seoul 07788, Republic of Korea.
2Department of Digital Healthcare, College of Health Sciences, Yonsei University, Wonju 26493, Republic of Korea.
3Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
PubMed PMC DOI PDF

Abstract

Background/Objectives: This study aimed to develop an artificial intelligence-based method for generating virtual post-contrast T1 maps and extracellular volume (ECV) maps from native T1 maps and to evaluate its performance. Methods: The proposed method was based on a modified self-consistent recursive diffusion bridge framework to generate virtual post-contrast T1 maps from native T1 maps. Cardia…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free AccountSign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.