Automatic Respiratory Self-Navigation Processing (ASAP) for Coronary MRA Using Principal Component Analysis

Keywords

abdominal accuracy added allow alternative although applications artery asap audience automatic axis binning bioengineering biomedical breathing calculating cedars clinical coefficients coil combination component consistent contains coronary correct correction correlation creates cross datasets defined desirable detect detected detection determine developing directly element engineering error essentially features five free funding grants health heart hence improve improvements in vivo inaccurate include inferior institute intervention investigation lacks larger largest linear liver lung make manual mask mass matches maximize modulation motion moving navigated navigation navigator need needed noise normalized northwestern novel numerical often onto orange outstanding pang part patient peak phantom pixels plays principal processing profile profiles projection promising proposed radial random readout regarded relevant reliability relies requiring researchers resolution respiratory robustness role scanner selection self sensitivity simple simulation sliding space strategy structure studies subsequent subsequently superior target template thresholding transformed translation translational true uncorrected unreliable upon user usually validation variance vectors visualization visually volume words yang yields