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Artificial intelligence-based Text-to-image Generation of Cardiac CT
- Source :
- Williams, M C, Williams, S & Newby, D E 2023, ' Artificial intelligence-based Text-to-image Generation of Cardiac CT ', Radiology: Cardiothoracic Imaging, vol. 5, no. 2, e220297 . https://doi.org/10.1148/ryct.220297, Radiol Cardiothorac Imaging
- Publication Year :
- 2023
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Abstract
- 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.
- Subjects :
- Radiology, Nuclear Medicine and imaging
Images in Cardiothoracic Imaging
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Williams, M C, Williams, S & Newby, D E 2023, ' Artificial intelligence-based Text-to-image Generation of Cardiac CT ', Radiology: Cardiothoracic Imaging, vol. 5, no. 2, e220297 . https://doi.org/10.1148/ryct.220297, Radiol Cardiothorac Imaging
- Accession number :
- edsair.doi.dedup.....33190751ff7a5100e59cb5f773244fcd
- Full Text :
- https://doi.org/10.1148/ryct.220297