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. 1809.10486
  4. Cited By
nnU-Net: Self-adapting Framework for U-Net-Based Medical Image
  Segmentation

nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation

27 September 2018
Fabian Isensee
Jens Petersen
André Klein
David Zimmerer
Paul F. Jaeger
Simon A. A. Kohl
Jakob Wasserthal
Gregor Koehler
T. Norajitra
Sebastian J. Wirkert
Klaus H. Maier-Hein
    SSeg
ArXivPDFHTML

Papers citing "nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation"

49 / 99 papers shown
Title
A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP)
  from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals
A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals
S. Mahmud
Nabil Ibtehaz
Amith Khandakar
Anas Tahir
Tawsifur Rahman
K. R. Islam
Md. Shafayet Hossain
M. S. Rahman
Mohammad Tariqul Islam
M. Chowdhury
26
52
0
12 Nov 2021
Hepatic vessel segmentation based on 3D swin-transformer with inductive
  biased multi-head self-attention
Hepatic vessel segmentation based on 3D swin-transformer with inductive biased multi-head self-attention
Mian Wu
Yinling Qian
Xiangyun Liao
Qiong Wang
Pheng-Ann Heng
MedIm
92
29
0
05 Nov 2021
Towards modelling hazard factors in unstructured data spaces using
  gradient-based latent interpolation
Towards modelling hazard factors in unstructured data spaces using gradient-based latent interpolation
Tobias Weber
Michael Ingrisch
Bernd Bischl
David Rügamer
17
1
0
21 Oct 2021
Transformer for Polyp Detection
Transformer for Polyp Detection
Shijie Liu
Hongyu Zhou
Xiaozhou Shi
Junwen Pan
ViT
MedIm
32
4
0
14 Oct 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
Self-Training Based Unsupervised Cross-Modality Domain Adaptation for
  Vestibular Schwannoma and Cochlea Segmentation
Self-Training Based Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation
Hyungseob Shin
Hyeongyu Kim
Sewon Kim
Yohan Jun
Taejoon Eo
D. Hwang
OOD
35
5
0
22 Sep 2021
ImageTBAD: A 3D Computed Tomography Angiography Image Dataset for
  Automatic Segmentation of Type-B Aortic Dissection
ImageTBAD: A 3D Computed Tomography Angiography Image Dataset for Automatic Segmentation of Type-B Aortic Dissection
Zeyang Yao
Jiawei Zhang
Hailong Qiu
Tianchen Wang
Yiyu Shi
Zhuang Jian
Yuhao Dong
Meiping Huang
Xiaowei Xu
31
28
0
01 Sep 2021
Efficient Medical Image Segmentation Based on Knowledge Distillation
Efficient Medical Image Segmentation Based on Knowledge Distillation
Dian Qin
Jiajun Bu
Zhe Liu
Xin Shen
Sheng Zhou
Jingjun Gu
Zhihong Wang
Lei Wu
Hui-Fen Dai
30
129
0
23 Aug 2021
A persistent homology-based topological loss for CNN-based multi-class
  segmentation of CMR
A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR
Nicholas Byrne
J. Clough
I. Valverde
Giovanni Montana
A. King
34
25
0
27 Jul 2021
Hepatocellular Carcinoma Segmentation from Digital Subtraction
  Angiography Videos using Learnable Temporal Difference
Hepatocellular Carcinoma Segmentation from Digital Subtraction Angiography Videos using Learnable Temporal Difference
Wenting Jiang
Y. Jiang
Lu Zhang
Changmiao Wang
Xiaoguang Han
Shuixing Zhang
Xiang Wan
Shuguang Cui
18
1
0
09 Jul 2021
Towards Robust General Medical Image Segmentation
Towards Robust General Medical Image Segmentation
Laura Alexandra Daza
Juan C. Pérez
Pablo Arbelaez
OOD
28
25
0
09 Jul 2021
Automatic size and pose homogenization with spatial transformer network
  to improve and accelerate pediatric segmentation
Automatic size and pose homogenization with spatial transformer network to improve and accelerate pediatric segmentation
Giammarco La Barbera
Pietro Gori
Haithem Boussaid
Bruno Belucci
A. Delmonte
Jeanne Goulin
S. Sarnacki
L. Rouet
Isabelle Bloch
ViT
MedIm
17
4
0
06 Jul 2021
Quality-Aware Memory Network for Interactive Volumetric Image
  Segmentation
Quality-Aware Memory Network for Interactive Volumetric Image Segmentation
Tianfei Zhou
Liulei Li
G. Bredell
Jianwu Li
E. Konukoglu
24
14
0
20 Jun 2021
Automatic CT Segmentation from Bounding Box Annotations using
  Convolutional Neural Networks
Automatic CT Segmentation from Bounding Box Annotations using Convolutional Neural Networks
Yuanpeng Liu
Qinglei Hui
Zhiyi Peng
S. Gong
D. Kong
11
4
0
29 May 2021
The Federated Tumor Segmentation (FeTS) Challenge
The Federated Tumor Segmentation (FeTS) Challenge
Sarthak Pati
Ujjwal Baid
M. Zenk
Brandon Edwards
Micah J. Sheller
...
Lena Maier-Hein
Jens Kleesiek
Bjoern H. Menze
Klaus Maier-Hein
Spyridon Bakas
FedML
OOD
43
72
0
12 May 2021
Weakly-Supervised Universal Lesion Segmentation with Regional Level Set
  Loss
Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss
Youbao Tang
Jinzheng Cai
K. Yan
Lingyun Huang
Guotong Xie
Jing Xiao
Jingjing Lu
Gigin Lin
Le Lu
47
25
0
03 May 2021
Evidential segmentation of 3D PET/CT images
Evidential segmentation of 3D PET/CT images
Ling Huang
S. Ruan
P. Decazes
Thierry Denoeux
3DPC
38
13
0
27 Apr 2021
Detection, growth quantification and malignancy prediction of pulmonary
  nodules using deep convolutional networks in follow-up CT scans
Detection, growth quantification and malignancy prediction of pulmonary nodules using deep convolutional networks in follow-up CT scans
Xavier Rafael-Palou
A. Aubanell
M. Ceresa
Vicent J. Ribas
Gemma Piella
M. A. G. Ballester
MedIm
13
3
0
26 Mar 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
393
0
08 Feb 2021
Comparing Deep Learning strategies for paired but unregistered
  multimodal segmentation of the liver in T1 and T2-weighted MRI
Comparing Deep Learning strategies for paired but unregistered multimodal segmentation of the liver in T1 and T2-weighted MRI
V. Couteaux
Mathilde Trintignac
O. Nempont
G. Pizaine
A. Vlachomitrou
P. Valette
L. Milot
Isabelle Bloch
11
3
0
18 Jan 2021
Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging
  Studies
Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging Studies
Jinzheng Cai
Youbao Tang
K. Yan
Adam P. Harrison
Jing Xiao
Gigin Lin
Le Lu
MedIm
36
29
0
09 Dec 2020
High-level Prior-based Loss Functions for Medical Image Segmentation: A
  Survey
High-level Prior-based Loss Functions for Medical Image Segmentation: A Survey
Rosana El Jurdia
Caroline Petitjean
P. Honeine
V. Cheplygina
F. Abdallah
SSeg
MedIm
33
79
0
16 Nov 2020
What is the best data augmentation for 3D brain tumor segmentation?
What is the best data augmentation for 3D brain tumor segmentation?
M. Cirillo
David Abramian
Anders Eklund
22
4
0
26 Oct 2020
Learning Loss for Test-Time Augmentation
Learning Loss for Test-Time Augmentation
Ildoo Kim
Younghoon Kim
Sungwoong Kim
OOD
18
90
0
22 Oct 2020
Modality-Pairing Learning for Brain Tumor Segmentation
Modality-Pairing Learning for Brain Tumor Segmentation
Yixin Wang
Yao Zhang
Feng Hou
Yang Liu
Jiang Tian
Cheng Zhong
Yang Zhang
Zhiqiang He
69
66
0
19 Oct 2020
Fast meningioma segmentation in T1-weighted MRI volumes using a
  lightweight 3D deep learning architecture
Fast meningioma segmentation in T1-weighted MRI volumes using a lightweight 3D deep learning architecture
D. Bouget
André Pedersen
Sayied Abdol Mohieb Hosainey
J. Vanel
O. Solheim
Ingerid Reinertsen
24
15
0
14 Oct 2020
Test-time Unsupervised Domain Adaptation
Test-time Unsupervised Domain Adaptation
Thomas Varsavsky
Mauricio Orbes-Arteaga
Carole H. Sudre
M. Graham
P. Nachev
M. Jorge Cardoso
OOD
19
55
0
05 Oct 2020
Medical Image Segmentation Using Deep Learning: A Survey
Medical Image Segmentation Using Deep Learning: A Survey
Risheng Wang
Tao Lei
Xiaogang Du
Yong Wan
Hongying Meng
A. Nandi
SSeg
OOD
33
544
0
28 Sep 2020
UXNet: Searching Multi-level Feature Aggregation for 3D Medical Image
  Segmentation
UXNet: Searching Multi-level Feature Aggregation for 3D Medical Image Segmentation
Yuanfeng Ji
Ruimao Zhang
Zhuguo Li
Jiamin Ren
Shaoting Zhang
Ping Luo
3DPC
11
23
0
16 Sep 2020
User-Guided Domain Adaptation for Rapid Annotation from User
  Interactions: A Study on Pathological Liver Segmentation
User-Guided Domain Adaptation for Rapid Annotation from User Interactions: A Study on Pathological Liver Segmentation
Ashwin Raju
Zhanghexuan Ji
Chi-Tung Cheng
Jinzheng Cai
Junzhou Huang
Jing Xiao
Le Lu
Chien-Hung Liao
Adam P. Harrison
36
13
0
05 Sep 2020
Robust Pancreatic Ductal Adenocarcinoma Segmentation with
  Multi-Institutional Multi-Phase Partially-Annotated CT Scans
Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans
Ling Zhang
Yu Shi
Jiawen Yao
Yun Bian
Kai Cao
D. Jin
Jing Xiao
Le Lu
19
20
0
24 Aug 2020
Self-Supervision with Superpixels: Training Few-shot Medical Image
  Segmentation without Annotation
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation
Cheng Ouyang
C. Biffi
Chia-Ju Chen
Turkay Kart
Huaqi Qiu
Daniel Rueckert
22
205
0
20 Jul 2020
Superpixel-Guided Label Softening for Medical Image Segmentation
Superpixel-Guided Label Softening for Medical Image Segmentation
Han Li
Dong Wei
Shilei Cao
Kai Ma
Liansheng Wang
Yefeng Zheng
19
22
0
17 Jul 2020
PGD-UNet: A Position-Guided Deformable Network for Simultaneous
  Segmentation of Organs and Tumors
PGD-UNet: A Position-Guided Deformable Network for Simultaneous Segmentation of Organs and Tumors
Ziqiang Li
Hong Pan
Yaping Zhu
•. A. K. Qin
12
20
0
02 Jul 2020
LAMP: Large Deep Nets with Automated Model Parallelism for Image
  Segmentation
LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation
Wentao Zhu
Can Zhao
Wenqi Li
H. Roth
Ziyue Xu
Daguang Xu
3DV
32
18
0
22 Jun 2020
Searching Learning Strategy with Reinforcement Learning for 3D Medical
  Image Segmentation
Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation
Dong Yang
H. Roth
Ziyue Xu
Fausto Milletari
Ling Zhang
Daguang Xu
22
45
0
10 Jun 2020
Neuro4Neuro: A neural network approach for neural tract segmentation
  using large-scale population-based diffusion imaging
Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging
Bo Li
M. Groot
Rebecca M. E. Steketee
R. Meijboom
M. Smits
Meike W. Vernooij
M. Ikram
Jiren Liu
W. Niessen
Esther E. Bron
MedIm
16
31
0
26 May 2020
Automatic lung segmentation in routine imaging is primarily a data
  diversity problem, not a methodology problem
Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem
J. Hofmanninger
F. Prayer
Jeanny Pan
Sebastian Rohrich
H. Prosch
Georg Langs
38
46
0
31 Jan 2020
One Network to Segment Them All: A General, Lightweight System for
  Accurate 3D Medical Image Segmentation
One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation
Mathias Perslev
Erik Dam
A. Pai
Christian Igel
SSeg
VLM
MedIm
19
82
0
05 Nov 2019
Penalizing small errors using an Adaptive Logarithmic Loss
Penalizing small errors using an Adaptive Logarithmic Loss
Chaitanya Kaul
Nick E. Pears
Hang Dai
Roderick Murray-Smith
S. Manandhar
19
9
0
22 Oct 2019
MIScnn: A Framework for Medical Image Segmentation with Convolutional
  Neural Networks and Deep Learning
MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning
Dominik Muller
Frank Kramer
20
117
0
21 Oct 2019
Deep Semantic Segmentation of Natural and Medical Images: A Review
Deep Semantic Segmentation of Natural and Medical Images: A Review
Saeid Asgari Taghanaki
Kumar Abhishek
Joseph Paul Cohen
Julien Cohen-Adad
Ghassan Hamarneh
SSeg
VLM
39
667
0
16 Oct 2019
3D U$^2$-Net: A 3D Universal U-Net for Multi-Domain Medical Image
  Segmentation
3D U2^22-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation
Chao Huang
Hu Han
Qingsong Yao
Shankuan Zhu
S. Kevin Zhou
OOD
SSeg
29
71
0
04 Sep 2019
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and
  Generalist Convolution Kernels
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels
Felix J. S. Bragman
Ryutaro Tanno
Sebastien Ourselin
Daniel C. Alexander
M. Jorge Cardoso
24
86
0
26 Aug 2019
Bayesian Generative Models for Knowledge Transfer in MRI Semantic
  Segmentation Problems
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems
Anna Kuzina
Evgenii Egorov
Evgeny Burnaev
MedIm
26
19
0
15 Aug 2019
Domain specific cues improve robustness of deep learning based
  segmentation of ct volumes
Domain specific cues improve robustness of deep learning based segmentation of ct volumes
Marie Kloenne
Sebastian Niehaus
L. Lampe
A. Merola
J. Reinelt
Ingo Roeder
N. Scherf
OOD
21
1
0
23 Jul 2019
Scalable Neural Architecture Search for 3D Medical Image Segmentation
Scalable Neural Architecture Search for 3D Medical Image Segmentation
Sungwoong Kim
Ildoo Kim
Sungbin Lim
Woonhyuk Baek
Chiheon Kim
Hyungjoon Cho
Boogeon Yoon
Taesup Kim
19
74
0
13 Jun 2019
Automated Design of Deep Learning Methods for Biomedical Image
  Segmentation
Automated Design of Deep Learning Methods for Biomedical Image Segmentation
Fabian Isensee
Paul F. Jäger
Simon A. A. Kohl
Jens Petersen
Klaus H. Maier-Hein
3DV
SSeg
29
170
0
17 Apr 2019
Brain Tumor Segmentation using an Ensemble of 3D U-Nets and Overall
  Survival Prediction using Radiomic Features
Brain Tumor Segmentation using an Ensemble of 3D U-Nets and Overall Survival Prediction using Radiomic Features
Xue Feng
Nicholas J. Tustison
C. Meyer
48
224
0
03 Dec 2018
Previous
12