4D cardiac CT is increasingly used to evaluate cardiac dynamics. Echocardiography and CMR have demonstrated the utility of longitudinal shortening (LS) measures. We demonstrate the ability of a recently published deep learning framework to automatically and accurately measure LS from CT for detection of wall motion abnormalities (WMA) and Mitral Annular Plane Systolic Excursion (MAPSE).100 clinical cineCT studies were evaluated by three experienced cardiac CT readers for presence of WMA: 50 for method development and 50 for testing. Previously developed convolutional neural network was used to automatically segment the LV bloodpool and to define the 2CH, 3CH, and 4CH long-axis imaging planes. LS was measured as the perimeter of the bloodpoo...
The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wa...
Myocardial strain analysis from cinematic magnetic resonance imaging (cine-MRI) data provides a more...
Objectives: The aim of this study was to evaluate whether a deep convolutional neural network (DCNN)...
4D cardiac CT is increasingly used to evaluate cardiac dynamics. Echocardiography and CMR have demon...
Introduction4D cardiac CT (cineCT) is increasingly used to evaluate cardiac dynamics. While echocard...
AimsTo develop an automated method for bloodpool segmentation and imaging plane re-slicing of cardia...
BackgroundThe presence of left ventricular (LV) wall motion abnormalities (WMA) is an independent in...
PurposeTo investigate whether endocardial regional shortening computed from four-dimensional (4D) CT...
BackgroundThe presence of left ventricular (LV) wall motion abnormalities (WMA) is an independent in...
Coronary Artery Disease (CAD) is the leading cause of morbidity and mortality in developed nations. ...
Cardiac MRI diagnosis of regional LV dysfunction relies on subjective interpretation of cine images ...
Cardiovascular disease is the leading cause of death in the United States. 30~50% of cardiovascular ...
PurposeTo assess the feasibility of a newly developed algorithm, called deep learning synthetic stra...
Background Global longitudinal shortening (GL‐Shortening) and the mitral annular plane systolic excu...
Objectives This study sought to examine if fully automated measurements of global longitudinal strai...
The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wa...
Myocardial strain analysis from cinematic magnetic resonance imaging (cine-MRI) data provides a more...
Objectives: The aim of this study was to evaluate whether a deep convolutional neural network (DCNN)...
4D cardiac CT is increasingly used to evaluate cardiac dynamics. Echocardiography and CMR have demon...
Introduction4D cardiac CT (cineCT) is increasingly used to evaluate cardiac dynamics. While echocard...
AimsTo develop an automated method for bloodpool segmentation and imaging plane re-slicing of cardia...
BackgroundThe presence of left ventricular (LV) wall motion abnormalities (WMA) is an independent in...
PurposeTo investigate whether endocardial regional shortening computed from four-dimensional (4D) CT...
BackgroundThe presence of left ventricular (LV) wall motion abnormalities (WMA) is an independent in...
Coronary Artery Disease (CAD) is the leading cause of morbidity and mortality in developed nations. ...
Cardiac MRI diagnosis of regional LV dysfunction relies on subjective interpretation of cine images ...
Cardiovascular disease is the leading cause of death in the United States. 30~50% of cardiovascular ...
PurposeTo assess the feasibility of a newly developed algorithm, called deep learning synthetic stra...
Background Global longitudinal shortening (GL‐Shortening) and the mitral annular plane systolic excu...
Objectives This study sought to examine if fully automated measurements of global longitudinal strai...
The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wa...
Myocardial strain analysis from cinematic magnetic resonance imaging (cine-MRI) data provides a more...
Objectives: The aim of this study was to evaluate whether a deep convolutional neural network (DCNN)...