ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1711.01468
  4. Cited By
Ensembles of Multiple Models and Architectures for Robust Brain Tumour
  Segmentation

Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation

4 November 2017
Konstantinos Kamnitsas
Wenjia Bai
Enzo Ferrante
Jingyu Sun
Matthew Sinclair
Nick Pawlowski
Martin Rajchl
Matthew C. H. Lee
Bernhard Kainz
Daniel Rueckert
Ben Glocker
    3DV
    AAML
    OOD
ArXivPDFHTML

Papers citing "Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation"

9 / 59 papers shown
Title
Survival prediction using ensemble tumor segmentation and transfer
  learning
Survival prediction using ensemble tumor segmentation and transfer learning
Mariano Cabezas
Sergi Valverde
Sandra González-Villá
Albert Clérigues
Mostafa Salem
Kaisar Kushibar
J. Bernal
A. Oliver
Xavier Llado
11
24
0
04 Oct 2018
No New-Net
No New-Net
Fabian Isensee
Philipp Kickingereder
Wolfgang Wick
Martin Bendszus
Klaus H. Maier-Hein
SSeg
37
395
0
27 Sep 2018
Shallow vs deep learning architectures for white matter lesion
  segmentation in the early stages of multiple sclerosis
Shallow vs deep learning architectures for white matter lesion segmentation in the early stages of multiple sclerosis
Francesco La Rosa
M. J. Fartaria
T. Kober
J. Richiardi
Cristina Granziera
Jean-Philippe Thiran
Meritxell Bach Cuadra
15
25
0
10 Sep 2018
Brain Tumor Segmentation and Tractographic Feature Extraction from
  Structural MR Images for Overall Survival Prediction
Brain Tumor Segmentation and Tractographic Feature Extraction from Structural MR Images for Overall Survival Prediction
Po-Yu Kao
Thuyen Ngo
Angela Zhang
Jefferson W. Chen
B. S. Manjunath
23
84
0
20 Jul 2018
Towards safe deep learning: accurately quantifying biomarker uncertainty
  in neural network predictions
Towards safe deep learning: accurately quantifying biomarker uncertainty in neural network predictions
Zach Eaton-Rosen
Felix J. S. Bragman
Sotirios Bisdas
Sebastien Ourselin
M. Jorge Cardoso
UQCV
23
85
0
22 Jun 2018
Adaptive feature recombination and recalibration for semantic
  segmentation: application to brain tumor segmentation in MRI
Adaptive feature recombination and recalibration for semantic segmentation: application to brain tumor segmentation in MRI
Sérgio Pereira
Victor Alves
Carlos Alberto Silva
25
46
0
06 Jun 2018
Attention U-Net: Learning Where to Look for the Pancreas
Attention U-Net: Learning Where to Look for the Pancreas
Ozan Oktay
Jo Schlemper
Loic Le Folgoc
M. J. Lee
M. Heinrich
...
Jingyu Sun
Nils Y. Hammerla
Bernhard Kainz
Ben Glocker
Daniel Rueckert
SSeg
39
4,949
0
11 Apr 2018
Fully Convolutional Network Ensembles for White Matter Hyperintensities
  Segmentation in MR Images
Fully Convolutional Network Ensembles for White Matter Hyperintensities Segmentation in MR Images
Hongwei Bran Li
Gongfa Jiang
Jianguo Zhang
Ruixuan Wang
Zhaolei Wang
Weishi Zheng
Bjoern H. Menze
34
194
0
14 Feb 2018
Fully Convolutional Multi-scale Residual DenseNets for Cardiac
  Segmentation and Automated Cardiac Diagnosis using Ensemble of Classifiers
Fully Convolutional Multi-scale Residual DenseNets for Cardiac Segmentation and Automated Cardiac Diagnosis using Ensemble of Classifiers
Mahendra Khened
Alex Varghese
Ganapathy Krishnamurthi
24
310
0
16 Jan 2018
Previous
12