# UTA studies deep learning to reduce radiation in cardiac CT angiography > UTA studies deep learning to reduce radiation in cardiac CT angiography. The University of Texas at Arlington’s three-year, $579,745 NIH project plans to combine deep learning and imaging physics to reconstruct multiphase coronary CT angiography at lower radiation doses. - Canonical URL: https://newsverum.com/en/news/uta-ai-deep-learning-cardiac-ct-radiation-study-october-2026 - Publisher: Newsverum - Section: Technology - Country: United States - Published: 2026-10-15T23:21:07+00:00 - Updated: 2026-10-15T23:21:07+00:00 - Event / data period: 2026-10-15 - Other editions: [Türkçe](https://newsverum.com/tr/news/uta-ai-deep-learning-cardiac-ct-radiation-study-october-2026.md), [العربية](https://newsverum.com/ar/news/uta-ai-deep-learning-cardiac-ct-radiation-study-october-2026.md), [Français](https://newsverum.com/fr/news/uta-ai-deep-learning-cardiac-ct-radiation-study-october-2026.md), [Español](https://newsverum.com/es/news/uta-ai-deep-learning-cardiac-ct-radiation-study-october-2026.md), [Deutsch](https://newsverum.com/de/news/uta-ai-deep-learning-cardiac-ct-radiation-study-october-2026.md), [Português](https://newsverum.com/pt/news/uta-ai-deep-learning-cardiac-ct-radiation-study-october-2026.md) UTA studies deep learning to reduce radiation in cardiac CT angiography. The University of Texas at Arlington’s three-year, $579,745 NIH project plans to combine deep learning and imaging physics to reconstruct multiphase coronary CT angiography at lower radiation doses. Researchers will first build a synthetic patient library, then assess diagnostic accuracy with computational modeling and a small human-observer study. Mayo Clinic is expected to provide patient data. No achieved dose reduction or patient-validated diagnostic performance has been reported. ## Data ### UTA studies deep learning to reduce radiation in cardiac CT angiography UTA studies deep learning to reduce radiation in cardiac CT angiography. The University of Texas at Arlington’s three-year, $579,745 NIH project plans to combine deep learning and imaging physics to reconstruct multiphase coronary CT angiography at lower radiation doses. Methodology: This event record summarizes the research report in the cited primary source. It distinguishes announced plans from completed, measured results. | date | label | description | status | |---|---|---|---| | 2026-10-15 | UTA studies deep learning to reduce radiation in cardiac CT angiography | UTA studies deep learning to reduce radiation in cardiac CT angiography. The University of Texas at Arlington’s three-year, $579,745 NIH project plans to combine deep learning and imaging physics to reconstruct multiphase coronary CT angiography at lower radiation doses. | occurred | Sources: · Download data: [JSON](https://newsverum.com/api/v1/articles/uta-ai-deep-learning-cardiac-ct-radiation-study-october-2026/data/source-event?lang=en&format=json) · [CSV](https://newsverum.com/api/v1/articles/uta-ai-deep-learning-cardiac-ct-radiation-study-october-2026/data/source-event?lang=en&format=csv) ### Announced research funding UTA studies deep learning to reduce radiation in cardiac CT angiography. The University of Texas at Arlington’s three-year, $579,745 NIH project plans to combine deep learning and imaging physics to reconstruct multiphase coronary CT angiography at lower radiation doses. Methodology: This event record summarizes the research report in the cited primary source. It distinguishes announced plans from completed, measured results. | label | value | unit | period | basis | value_qualifier | |---|---|---|---|---|---| | Announced grant amount | 579745 | USD | 2026-10-15 | observed | exact | Sources: · Download data: [JSON](https://newsverum.com/api/v1/articles/uta-ai-deep-learning-cardiac-ct-radiation-study-october-2026/data/announced-funding?lang=en&format=json) · [CSV](https://newsverum.com/api/v1/articles/uta-ai-deep-learning-cardiac-ct-radiation-study-october-2026/data/announced-funding?lang=en&format=csv) ## Sources - [University of Texas at Arlington]() (Source checked: 2026-10-15; Published: 2026-10-15) --- Cite the canonical URL above. [Editorial standards and corrections](https://newsverum.com/en/editorial)