Anastasio Lab

Research focus

NIH R01 · 2025

Deep learning technologies for estimating the optimal task performance of medical imaging systems

ABSTRACT Modern medical imaging systems comprise complicated hardware and sophisticated computational methods. Given the sheer number of system parameters that impact image quality, the large variety in objects to be imaged, and ethical concerns, the assessment and refinement of emerging imaging technologies via clinical trials often is impossible. For these reasons, there is great interest in virtual imaging trials (VITs) that permit the automated simulation and analysis of clinically relevant imaging experiments. During the development and refinement of new imaging technologies via VITs, there is an important need for assessing objective image quality measures (OIQMs) that quantify the…

From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.