Deep learning for cardiac image segmentation: a review

C Chen, C Qin, H Qiu, G Tarroni, J Duan… - Frontiers in …, 2020 - frontiersin.org
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 …

A survey on U-shaped networks in medical image segmentations

L Liu, J Cheng, Q Quan, FX Wu, YP Wang, J Wang - Neurocomputing, 2020 - Elsevier
The U-shaped network is one of the end-to-end convolutional neural networks (CNNs). In
electron microscope segmentation of ISBI challenge 2012, the concise architecture and …

Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?

O Bernard, A Lalande, C Zotti… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac
magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish …

Learning active contour models for medical image segmentation

X Chen, BM Williams… - Proceedings of the …, 2019 - openaccess.thecvf.com
Image segmentation is an important step in medical image processing and has been widely
studied and developed for refinement of clinical analysis and applications. New models …

Fully convolutional multi-scale residual DenseNets for cardiac segmentation and automated cardiac diagnosis using ensemble of classifiers

M Khened, VA Kollerathu, G Krishnamurthi - Medical image analysis, 2019 - Elsevier
Deep fully convolutional neural network (FCN) based architectures have shown great
potential in medical image segmentation. However, such architectures usually have millions …

Cardiac segmentation with strong anatomical guarantees

N Painchaud, Y Skandarani, T Judge… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Convolutional neural networks (CNN) have had unprecedented success in medical imaging
and, in particular, in medical image segmentation. However, despite the fact that …

Convolutional neural network with shape prior applied to cardiac MRI segmentation

C Zotti, Z Luo, A Lalande… - IEEE journal of biomedical …, 2018 - ieeexplore.ieee.org
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 …

3-D consistent and robust segmentation of cardiac images by deep learning with spatial propagation

Q Zheng, H Delingette, N Duchateau… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
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 …

Saunet: Shape attentive u-net for interpretable medical image segmentation

J Sun, F Darbehani, M Zaidi, B Wang - … , Lima, Peru, October 4–8, 2020 …, 2020 - Springer
Medical image segmentation is a difficult but important task for many clinical operations such
as cardiac bi-ventricular volume estimation. More recently, there has been a shift to utilizing …

High-level prior-based loss functions for medical image segmentation: A survey

R El Jurdi, C Petitjean, P Honeine, V Cheplygina… - Computer Vision and …, 2021 - Elsevier
Today, deep convolutional neural networks (CNNs) have demonstrated state of the art
performance for supervised medical image segmentation, across various imaging modalities …