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Automatic quantification of the LV function and mass: a deep learning
  approach for cardiovascular MRI

Automatic quantification of the LV function and mass: a deep learning approach for cardiovascular MRI

14 December 2018
A. Curiale
F. D. Colavecchia
G. Mato
ArXivPDFHTML

Papers citing "Automatic quantification of the LV function and mass: a deep learning approach for cardiovascular MRI"

4 / 4 papers shown
Title
Automatic Quantification of Volumes and Biventricular Function in
  Cardiac Resonance. Validation of a New Artificial Intelligence Approach
Automatic Quantification of Volumes and Biventricular Function in Cardiac Resonance. Validation of a New Artificial Intelligence Approach
A. Curiale
Matías Calandrelli
Lucca Dellazoppa
Mariano Trevisan
Jorge Luis BociÁn
Juan Pablo Bonifacio
G. Mato
22
0
0
03 Jun 2022
U-Net and its variants for medical image segmentation: theory and
  applications
U-Net and its variants for medical image segmentation: theory and applications
N. Siddique
Sidike Paheding
Colin P. Elkin
Vijay Devabhaktuni
SSeg
28
1,044
0
02 Nov 2020
Post-DAE: Anatomically Plausible Segmentation via Post-Processing with
  Denoising Autoencoders
Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders
Agostina J. Larrazabal
Cesar E. Martínez
Ben Glocker
Enzo Ferrante
27
65
0
24 Jun 2020
A Survey on Deep Learning in Medical Image Analysis
A Survey on Deep Learning in Medical Image Analysis
G. Litjens
Thijs Kooi
B. Bejnordi
A. Setio
F. Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
C. I. Sánchez
OOD
337
10,633
0
19 Feb 2017
1