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Brain tumor segmentation with self-ensembled, deeply-supervised 3D U-net
  neural networks: a BraTS 2020 challenge solution

Brain tumor segmentation with self-ensembled, deeply-supervised 3D U-net neural networks: a BraTS 2020 challenge solution

30 October 2020
T. Henry
Alexandre Carré
Marvin Lerousseau
Théo Estienne
C. Robert
Nikos Paragios
Eric Deutsch
ArXivPDFHTML

Papers citing "Brain tumor segmentation with self-ensembled, deeply-supervised 3D U-net neural networks: a BraTS 2020 challenge solution"

12 / 12 papers shown
Title
Cross-dimensional transfer learning in medical image segmentation with
  deep learning
Cross-dimensional transfer learning in medical image segmentation with deep learning
Hicham Messaoudi
Ahror Belaid
Douraied BEN SALEM
Pierre-Henri Conze
MedIm
30
24
0
29 Jul 2023
The Segment Anything foundation model achieves favorable brain tumor
  autosegmentation accuracy on MRI to support radiotherapy treatment planning
The Segment Anything foundation model achieves favorable brain tumor autosegmentation accuracy on MRI to support radiotherapy treatment planning
F. Putz
J. Grigo
T. Weissmann
P. Schubert
D. Hoefler
...
L. Distel
S. Semrau
Christoph Bert
R. Fietkau
Yixing Huang
22
18
0
16 Apr 2023
DIGEST: Deeply supervIsed knowledGE tranSfer neTwork learning for brain
  tumor segmentation with incomplete multi-modal MRI scans
DIGEST: Deeply supervIsed knowledGE tranSfer neTwork learning for brain tumor segmentation with incomplete multi-modal MRI scans
Haoran Li
Cheng Li
Weijian Huang
Xiawu Zheng
Yantao Xi
Shanshan Wang
MedIm
28
2
0
15 Nov 2022
Deep Superpixel Generation and Clustering for Weakly Supervised
  Segmentation of Brain Tumors in MR Images
Deep Superpixel Generation and Clustering for Weakly Supervised Segmentation of Brain Tumors in MR Images
Jayeon Yoo
Khashayar Namdar
Farzad Khalvati
21
2
0
20 Sep 2022
A Neural Ordinary Differential Equation Model for Visualizing Deep
  Neural Network Behaviors in Multi-Parametric MRI based Glioma Segmentation
A Neural Ordinary Differential Equation Model for Visualizing Deep Neural Network Behaviors in Multi-Parametric MRI based Glioma Segmentation
Zhenyu Yang
Zongsheng Hu
H. Ji
Kyle J. Lafata
Scott Floyd
F. Yin
Cong Wang
26
14
0
01 Mar 2022
Optimizing Prediction of MGMT Promoter Methylation from MRI Scans using
  Adversarial Learning
Optimizing Prediction of MGMT Promoter Methylation from MRI Scans using Adversarial Learning
Sauman Das
AI4CE
19
6
0
12 Jan 2022
Improving the Segmentation of Pediatric Low-Grade Gliomas through
  Multitask Learning
Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning
Partoo Vafaeikia
M. Wagner
U. Tabori
B. Ertl-Wagner
Farzad Khalvati
11
6
0
29 Nov 2021
BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor
  Segmentation
BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor Segmentation
Qiran Jia
Hai Shu
ViT
MedIm
98
69
0
25 Sep 2021
Unified Focal loss: Generalising Dice and cross entropy-based losses to
  handle class imbalanced medical image segmentation
Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation
Michael Yeung
Evis Sala
Carola-Bibiane Schönlieb
L. Rundo
32
394
0
08 Feb 2021
Bag of Tricks for Image Classification with Convolutional Neural
  Networks
Bag of Tricks for Image Classification with Convolutional Neural Networks
Tong He
Zhi-Li Zhang
Hang Zhang
Zhongyue Zhang
Junyuan Xie
Mu Li
221
1,399
0
04 Dec 2018
There Are Many Consistent Explanations of Unlabeled Data: Why You Should
  Average
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
Ben Athiwaratkun
Marc Finzi
Pavel Izmailov
A. Wilson
208
243
0
14 Jun 2018
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
270
1,275
0
06 Mar 2017
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