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An End-to-end Approach to Semantic Segmentation with 3D CNN and
  Posterior-CRF in Medical Images

An End-to-end Approach to Semantic Segmentation with 3D CNN and Posterior-CRF in Medical Images

8 November 2018
Shuai Chen
Marleen de Bruijne
    MedIm
ArXiv (abs)PDFHTML

Papers citing "An End-to-end Approach to Semantic Segmentation with 3D CNN and Posterior-CRF in Medical Images"

5 / 5 papers shown
A survey on shape-constraint deep learning for medical image
  segmentation
A survey on shape-constraint deep learning for medical image segmentationIEEE Reviews in Biomedical Engineering (IEEE Rev. Biomed. Eng.), 2021
Simon Bohlender
Ilkay Oksuz
Anirban Mukhopadhyay
3DV
317
60
0
19 Jan 2021
MeDaS: An open-source platform as service to help break the walls
  between medicine and informatics
MeDaS: An open-source platform as service to help break the walls between medicine and informatics
Liang Zhang
Johann Li
Ping Li
Xiaoyuan Lu
Peiyi Shen
Guangming Zhu
Syed Afaq Ali Shah
Bennamoun
Kun Qian
Björn W. Schuller
MedIm
287
7
0
12 Jul 2020
Globally Optimal Surface Segmentation using Deep Learning with Learnable
  Smoothness Priors
Globally Optimal Surface Segmentation using Deep Learning with Learnable Smoothness Priors
Leixin Zhou
Xiaodong Wu
80
1
0
02 Jul 2020
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for
  Medical Image Segmentation
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation
Nima Tajbakhsh
Laura Jeyaseelan
Cunliang Kong
J. Chiang
Zhihao Wu
Xiaowei Ding
516
937
0
27 Aug 2019
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy
Christian Wachinger
M. Reuter
T. Klein
3DV
653
342
0
27 Feb 2017
1
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