Inline SNR-driven automatic quality control of UTE pulmonary imaging for patient-specific scan time adaptation

Motivation: Image quality with fixed scan-duration is patient-dependent, leading to potentially insufficient quality for some patients and unnecessarily long scan time for others. Goal(s): We propose inline automatic quality control based on signal-to-noise ratio (SNR) to efficiently achieve consistent diagnostic image quality for 3D pulmonary imaging. Approach: We designed a closed-loop feedback framework between image reconstruction and data acquisition to automatically stop the acquisition when a target SNR is achieved. 6 healthy volunteers (HV) were imaged at 0.55T. Results: Target SNR was achieved at 3mins 57s±1min 9s across the population. Impact: The inline automatic quality control enables a subject-specific optimized scan time while ensuring sufficient data for highly resolved complex reconstruction. The distribution of early stopping times (1min 9s) across the population revealed the value of subject-specific scan time.