Fatemeh Salehi Moghaddam, Shahnaz TorkZahrani, Azam Moslemi, Seyyed Ali Azin, Giti Ozgoli, Narges Joulaee Rad
Effectiveness of Sexual Skills Training Program on Promoting Sexual Intimacy and Satisfaction in Women in Tehran (Iran): A randomized clinical Trial Study
Urology journal
purpose develop deep learning model increasing cardiac cine frame rate maintaining spatial resolution scan time materials methods transformerbased model trained tested retrospective sample cine images 5840 patients mean age 55 years 19 sd 3527 male patients referred clinical cardiac mri 2003 2021 nine centers images acquired using 15 3t scanners three vendors data three centers used training testing 41 ratio remaining data used external testing cines downsampled frame rates restored using linear bicubic modelbased interpolation root mean square error interpolated original cine images modeled using ordinary least squares regression prospective study 49 participants referred clinical cardiac mri mean age 56 years 13 25 male participants 12 healthy participants mean age 51 years 16 eight male participants model applied cines acquired 25 frames per second fps thereby doubling frame rate interpolated cines compared actual 50fps cines preference two readers based perceived temporal smoothness image quality evaluated using noninferiority margin 10 results model generated artifactfree interpolated images ordinary least squares regression analysis accounting vendor field strength showed lower error p 001 modelbased interpolation compared linear bicubic interpolation internal external test sets highest proportion reader choices preference 84 122 actual interpolated 50fps cines 90 ci difference reader proportions favoring collected 15 122 interpolated 23 122 highframerate cines 001 014 indicating noninferiority conclusion transformerbased deep learning model increased cardiac cine frame rates preserving spatial resolution scan time resulting images quality comparable images obtained actual high frame rates keywords functional mri heart cardiac deep learning high frame rate supplemental material available article rsna 2024