Artificial intelligence-based Text-to-image Generation of Cardiac CT

Michelle C Williams*, Steven Williams, David E Newby

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Artificial intelligence (AI) has revolutionized art and design industries due to its ability to create images from natural language text. Such models also contain latent medical information. Text-to-image AI thus has the potential to create synthetic data sets for research, education, and communication. However, these may be indistinguishable from real images, causing issues with trust and potential misrepresentation. Radiologists and clinicians must be aware of the feasibility of creating “deep fake” medical images (Figure). Inconsistencies in anatomy or image texture could identify AI images, but there are currently no technical solutions for identification.
Original languageEnglish
Article numbere220297
JournalRadiology: Cardiothoracic Imaging
Issue number2
Publication statusPublished - 6 Apr 2023


Dive into the research topics of 'Artificial intelligence-based Text-to-image Generation of Cardiac CT'. Together they form a unique fingerprint.

Cite this