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ISLES 2022: A multi-center magnetic resonance imaging stroke lesion
  segmentation dataset

ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset

14 June 2022
M. H. Petzsche
Ezequiel de la Rosa
U. Hanning
Roland Wiest
Waldo Enrique Valenzuela Pinilla
M. Reyes
Maria Inês Meyer
S. Liew
Florian Kofler
Ivan Ezhov
D. Robben
Alexander Hutton
Tassilo Friedrich
Teresa Zarth
Johannes Bürkle
The Anh Baran
Bjoern Menze
G. Broocks
L. Meyer
C. Zimmer
T. Boeckh-Behrens
M. Berndt
B. Ikenberg
Benedikt Wiestler
Jan S. Kirschke
    OOD
ArXiv (abs)PDFHTML

Papers citing "ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset"

9 / 9 papers shown
Title
Revisiting MAE pre-training for 3D medical image segmentation
Revisiting MAE pre-training for 3D medical image segmentation
Tassilo Wald
Constantin Ulrich
Stanislav Lukyanenko
Andrei Goncharov
Alberto Paderno
Leander Maerkisch
Paul F. Jäger
Paul F. Jäger
Klaus Maier-Hein
95
2
0
30 Oct 2024
Autoregressive Sequence Modeling for 3D Medical Image Representation
Autoregressive Sequence Modeling for 3D Medical Image Representation
Siwen Wang
Churan Wang
Fei Gao
Lixian Su
Fandong Zhang
Yizhou Wang
Yizhou Yu
MedIm
107
1
0
13 Sep 2024
How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model
How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model
Han Gu
Haoyu Dong
Jichen Yang
Maciej A. Mazurowski
MedImVLM
129
20
0
15 Apr 2024
One Model to Rule them All: Towards Universal Segmentation for Medical Images with Text Prompts
One Model to Rule them All: Towards Universal Segmentation for Medical Images with Text Prompts
Ziheng Zhao
Yao Zhang
Chaoyi Wu
Xiaoman Zhang
Ya Zhang
Yanfeng Wang
Weidi Xie
VLMMedIm
110
40
0
28 Dec 2023
Differentiable Deconvolution for Improved Stroke Perfusion Analysis
Differentiable Deconvolution for Improved Stroke Perfusion Analysis
Ezequiel de la Rosa
D. Robben
Diana Sima
Jan S. Kirschke
Bjoern Menze
21
6
0
31 Mar 2021
AIFNet: Automatic Vascular Function Estimation for Perfusion Analysis
  Using Deep Learning
AIFNet: Automatic Vascular Function Estimation for Perfusion Analysis Using Deep Learning
Ezequiel de la Rosa
Diana Sima
Bjoern Menze
Jan S. Kirschke
D. Robben
60
14
0
04 Oct 2020
Automated brain extraction of multi-sequence MRI using artificial neural
  networks
Automated brain extraction of multi-sequence MRI using artificial neural networks
Fabian Isensee
Marianne Schell
I. Tursunova
G. Brugnara
D. Bonekamp
...
S. Heiland
Wolfgang Wick
Martin Bendszus
Klaus Hermann Maier-Hein
Philipp Kickingereder
80
492
0
31 Jan 2019
Prediction of final infarct volume from native CT perfusion and
  treatment parameters using deep learning
Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning
D. Robben
A. Boers
H. Marquering
L. Langezaal
Y. Roos
...
D. Dippel
C. Majoie
A. van der Lugt
Robin Lemmens
P. Suetens
39
72
0
06 Dec 2018
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
Özgün Çiçek
Ahmed Abdulkadir
S. Lienkamp
Thomas Brox
Olaf Ronneberger
3DV3DPCSSeg3DH
157
6,556
0
21 Jun 2016
1