Time-resolved tracking of the atrioventricular plane displacement in long-axis cine images with residual neural networks
Gonzales RA., Onofrey J., Lamy J., Seemann F., Heiberg E., Peters DC.
Diastolic dysfunction is assessed by measurement of mitral annular (MA) early diastolic velocity (e’), commonly performed in echocardiography. Similar measurements can be obtained with valvular plane tracking in MRI long-axis cines. These measurements have been validated and have good reproducibility, yet manual MA points annotations are required. In this work we present a machine learning convolutional neural network with a residual architecture for automatic annotation of MA points in MRI long-axis cine images of the 2 and 4-chamber views. The landmark tracking allowed a fast and accurate evaluation of diastolic parameters improving the clinical applicability of MRI for diastolic assessment.