Search results for "Ventricular cavity"
showing 3 items of 3 documents
Automatic Myocardial Infarction Evaluation from Delayed-Enhancement Cardiac MRI Using Deep Convolutional Networks
2021
In this paper, we propose a new deep learning framework for an automatic myocardial infarction evaluation from clinical information and delayed enhancement-MRI (DE-MRI). The proposed framework addresses two tasks. The first task is automatic detection of myocardial contours, the infarcted area, the no-reflow area, and the left ventricular cavity from a short-axis DE-MRI series. It employs two segmentation neural networks. The first network is used to segment the anatomical structures such as the myocardium and left ventricular cavity. The second network is used to segment the pathological areas such as myocardial infarction, myocardial no-reflow, and normal myocardial region. The segmented …
A 3D Network Based Shape Prior for Automatic Myocardial Disease Segmentation in Delayed-Enhancement MRI
2021
Abstract Objectives: In this work, a new deep learning model for relevant myocardial infarction segmentation from Late Gadolinium Enhancement (LGE)-MRI is proposed. Moreover, our novel segmentation method aims to detect microvascular-obstructed regions accurately. Material and methods: We first segment the anatomical structures, i.e., the left ventricular cavity and the myocardium, to achieve a preliminary segmentation. Then, a shape prior based framework that fuses the 3D U-Net architecture with 3D Autoencoder segmentation framework to constrain the segmentation process of pathological tissues is applied. Results: The proposed network reached outstanding myocardial segmentation compared wi…
Color superposition: a new modality for contrast echocardiography.
1987
To improve the estimation of endocardial borders in echocardiography, a technique has been developed to combine images from contrasted and noncontrasted echocardiograms of the same heart-phase using a color superposition mode. This method allows both experienced as well as less experienced examiners to define the endocardial borders more reproducibly and objectively. This is achieved by displaying tissue structures as gray level images while the ventricular cavity is marked selectively by the color display of the contrast material zone. Results of volume estimations of the left ventricle by different examiners using several imaging modes including color superposition display are presented.