Recurrent fully convolutional neural networks for multi-slice MRI cardiac segmentation
In cardiac magnetic resonance imaging, fully-automatic segmentation of the heart enables
precise structural and functional measurements to be taken, eg from short-axis MR images …
precise structural and functional measurements to be taken, eg from short-axis MR images …
2D-3D fully convolutional neural networks for cardiac MR segmentation
In this paper, we develop a 2D and 3D segmentation pipelines for fully automated cardiac
MR image segmentation using Deep Convolutional Neural Networks (CNN). Our models are …
MR image segmentation using Deep Convolutional Neural Networks (CNN). Our models are …
An exploration of 2D and 3D deep learning techniques for cardiac MR image segmentation
Accurate segmentation of the heart is an important step towards evaluating cardiac function.
In this paper, we present a fully automated framework for segmentation of the left (LV) and …
In this paper, we present a fully automated framework for segmentation of the left (LV) and …
A fully convolutional neural network for cardiac segmentation in short-axis MRI
PV Tran - arXiv preprint arXiv:1604.00494, 2016 - arxiv.org
Automated cardiac segmentation from magnetic resonance imaging datasets is an essential
step in the timely diagnosis and management of cardiac pathologies. We propose to tackle …
step in the timely diagnosis and management of cardiac pathologies. We propose to tackle …
3-D consistent and robust segmentation of cardiac images by deep learning with spatial propagation
We propose a method based on deep learning to perform cardiac segmentation on short
axis Magnetic resonance imaging stacks iteratively from the top slice (around the base) to …
axis Magnetic resonance imaging stacks iteratively from the top slice (around the base) to …
A distance map regularized CNN for cardiac cine MR image segmentation
Purpose Cardiac image segmentation is a critical process for generating personalized
models of the heart and for quantifying cardiac performance parameters. Fully automatic …
models of the heart and for quantifying cardiac performance parameters. Fully automatic …
Convolutional neural network with shape prior applied to cardiac MRI segmentation
In this paper, we present a novel convolutional neural network architecture to segment
images from a series of short-axis cardiac magnetic resonance slices (CMRI). The proposed …
images from a series of short-axis cardiac magnetic resonance slices (CMRI). The proposed …
Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M&Ms challenge
The emergence of deep learning has considerably advanced the state-of-the-art in cardiac
magnetic resonance (CMR) segmentation. Many techniques have been proposed over the …
magnetic resonance (CMR) segmentation. Many techniques have been proposed over the …
GridNet with automatic shape prior registration for automatic MRI cardiac segmentation
In this paper, we propose a fully automatic MRI cardiac segmentation method based on a
novel deep convolutional neural network (CNN) designed for the 2017 ACDC MICCAI …
novel deep convolutional neural network (CNN) designed for the 2017 ACDC MICCAI …
Improving the generalizability of convolutional neural network-based segmentation on CMR images
Background: Convolutional neural network (CNN) based segmentation methods provide an
efficient and automated way for clinicians to assess the structure and function of the heart in …
efficient and automated way for clinicians to assess the structure and function of the heart in …