Deep learning for cardiac image segmentation: a review
Deep learning has become the most widely used approach for cardiac image segmentation
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
Review of deep learning approaches for the segmentation of multiple sclerosis lesions on brain MRI
In recent years, there have been multiple works of literature reviewing methods for
automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature …
automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature …
Causal knowledge fusion for 3D cross-modality cardiac image segmentation
Abstract Three-dimensional (3D) cross-modality cardiac image segmentation is critical for
cardiac disease diagnosis and treatment. However, it confronts the challenge of modality …
cardiac disease diagnosis and treatment. However, it confronts the challenge of modality …
[HTML][HTML] FA-GAN: Fused attentive generative adversarial networks for MRI image super-resolution
High-resolution magnetic resonance images can provide fine-grained anatomical
information, but acquiring such data requires a long scanning time. In this paper, a …
information, but acquiring such data requires a long scanning time. In this paper, a …
Cardiovascular disease diagnosis from DXA scan and retinal images using deep learning
Cardiovascular diseases (CVD) are the leading cause of death worldwide. People affected
by CVDs may go undiagnosed until the occurrence of a serious heart failure event such as …
by CVDs may go undiagnosed until the occurrence of a serious heart failure event such as …
An open IoHT-based deep learning framework for online medical image recognition
CMJM Dourado, SPP da Silva… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
Systems developed to work with computational intelligence have become very efficient, and
in some cases obtain more accurate results than evaluations by humans. Hence, this work …
in some cases obtain more accurate results than evaluations by humans. Hence, this work …
Learning physical properties in complex visual scenes: An intelligent machine for perceiving blood flow dynamics from static CT angiography imaging
Humans perceive physical properties such as motion and elastic force by observing objects
in visual scenes. Recent research has proven that computers are capable of inferring …
in visual scenes. Recent research has proven that computers are capable of inferring …
[HTML][HTML] Simultaneous left atrium anatomy and scar segmentations via deep learning in multiview information with attention
Three-dimensional late gadolinium enhanced (LGE) cardiac MR (CMR) of left atrial scar in
patients with atrial fibrillation (AF) has recently emerged as a promising technique to stratify …
patients with atrial fibrillation (AF) has recently emerged as a promising technique to stratify …
BMAnet: Boundary mining with adversarial learning for semi-supervised 2D myocardial infarction segmentation
Automatic segmentation of myocardial infarction (MI) regions in late gadolinium-enhanced
cardiac magnetic resonance images is an essential step in the computed diagnosis of …
cardiac magnetic resonance images is an essential step in the computed diagnosis of …
Deep learning analysis in coronary computed tomographic angiography imaging for the assessment of patients with coronary artery stenosis
Abstract Background and Objective Recently, deep convolutional neural network has
significantly improved image classification and image segmentation. If coronary artery …
significantly improved image classification and image segmentation. If coronary artery …