A New Framework for Performing Cardiac Strain Analysis from Cine MRI Imaging in Mice.

ABSTRACT: Cardiac magnetic resonance (MR) imaging is one of the most rigorous form of imaging to assess cardiac function in vivo. Strain analysis allows comprehensive assessment of diastolic myocardial function, which is not indicated by measuring systolic functional parameters using with a normal cine imaging module. Due to the small heart size in mice, it is not possible to perform proper tagged imaging to assess strain. Here, we developed a novel deep learning approach for automated quantification of strain from cardiac cine MR images. Our framework starts by an accurate localization of the LV blood pool center-point using a fully convolutional neural network (FCN) architecture. Then, a region of interest (ROI) that contains the LV is extracted from all heart sections. The extracted ROIs are used

SUBMITTER: Hammouda K 

PROVIDER: S-EPMC7205890 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature