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Segmentation of the Myocardium on Late-Gadolinium Enhanced MRI based on
  2.5 D Residual Squeeze and Excitation Deep Learning Model

Segmentation of the Myocardium on Late-Gadolinium Enhanced MRI based on 2.5 D Residual Squeeze and Excitation Deep Learning Model

27 May 2020
Abdul Qayyum
A. Lalande
Thomas Decourselle
T. Pommier
A. Cochet
F. Mériaudeau
ArXiv (abs)PDFHTML

Papers citing "Segmentation of the Myocardium on Late-Gadolinium Enhanced MRI based on 2.5 D Residual Squeeze and Excitation Deep Learning Model"

4 / 4 papers shown
Title
Atrial Scar Quantification via Multi-scale CNN in the Graph-cuts
  Framework
Atrial Scar Quantification via Multi-scale CNN in the Graph-cuts Framework
Lei Li
Fuping Wu
Guang Yang
Lingchao Xu
T. Wong
R. Mohiaddin
D. Firmin
J. Keegan
Xiahai Zhuang
MedIm
46
69
0
21 Feb 2019
Recalibrating Fully Convolutional Networks with Spatial and Channel
  'Squeeze & Excitation' Blocks
Recalibrating Fully Convolutional Networks with Spatial and Channel 'Squeeze & Excitation' Blocks
Abhijit Guha Roy
Nassir Navab
Christian Wachinger
SSeg
113
380
0
23 Aug 2018
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image
  Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan
Alex Kendall
R. Cipolla
SSeg
1.1K
15,819
0
02 Nov 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg3DV
1.9K
77,378
0
18 May 2015
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