State-of-the-art medical image segmentation methods based on various challenges! (Updated 202101) Head and Neck
2020 MICCAI: Retinal Fundus Glaucoma Challenge Edition2 (REFUGE2) (Results)
2020 MICCAI: Brain Tumor Segmentation Challenge (BraTS) (Results)
2020 MICCAI: CATARACTS Semantic Segmentation
2020 MICCAI: Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images (ABCs) (Results)
2020 MICCAI: 3D Head and Neck Tumor Segmentation (HECKTOR) (Results)
2020 MICCAI: Cerebral Aneurysm Segmentation (CADA) (Results)
2020 MICCAI: Aneurysm Detection And segMenation Challenge 2020 (ADAM) (Results)
2020 MICCAI: Thyroid nodule segmentation and classification challenge (TN-SCUI 2020) . (Results)
2020 ICIAR: Automatic Lung Cancer Patient Management (LNDb) (LNDb)
2019 MICCAI: Multimodal Brain Tumor Segmentation Challenge (BraTS2019) (Results)
2019 MICCAI: 6-month Infant Brain MRI Segmentation from Multiple Sites (iSeg2019) (Results)
2019 MICCAI: Automatic Structure Segmentation for Radiotherapy Planning Challenge (Results)
2018 MICCAI: Multimodal Brain Tumor Segmentation Challenge
2018 MICCAI: Ischemic stroke lesion segmentation
2018 MICCAI Grand Challenge on MR Brain Image Segmentation
Chest & Abdomen
2020 MICCAI: Large Scale Vertebrae Segmentation Challenge (VerSe) (Results)
2020 MICCAI: Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI (EMIDEC)
2020 MICCAI: Automated Segmentation of Coronary Arteries (ASOCA) (Results)
2020 MICCAI: MyoPS 2020: Myocardial pathology segmentation combining multi-sequence CMR (Homepage)
2019 MICCAI: VerSe2019: Large Scale Vertebrae Segmentation Challenge (Results)
2019 MICCAI: Multi-sequence Cardiac MR Segmentation Challenge
2018 MICCAI: Left Ventricle Full Quantification Challenge
2018 MICCAI: Atrial Segmentation Challenge
2019 MICCAI: Kidney Tumor Segmentation Challenge
2019 ISBI: Segmentation of THoracic Organs at Risk in CT images
2017 ISBI & MICCAI: Liver tumor segmentation challenge
2012 MICCAI: Prostate MR Image Segmentation
Others
2018 MICCAI: Medical Segmentation Decathlon (MSD) (Results)
2020 MICCAI: Quantification of Uncertainties in Biomedical Image Quantification Challenge (QUBIQ) (Results)
Awesome Open Source Tools
Loss Odyssey in Medical Image Segmentation
Survey
@article{Ma-SOTASeg2020,
title={Cutting-edge 3D Medical Image Segmentation Methods in 2020: Are Happy Families All Alike?},
author={Jun Ma},
journal={arXiv preprint arXiv:2101.00232},
year={2021}
}
Date
First Author
Title
IoU
HD
MD
Remark
20201008
Mediclouds
TBA
0.758
2.866
1.618
1st Place in MICCAI 2020
20201008
Jun Ma
Exploring Large Context for Cerebral Aneurysm Segmentation (arxiv) (Code)
0.759
4.967
3.535
2nd Place in MICCAI 2020
2020 MICCAI: Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI (EMIDEC)
Date
First Author
Title
Myo
Infarction
Re-flow
Remark
20201008
Yichi Zhang
Cascaded Convolutional Neural Network for Automatic Myocardial Infarction Segmentation from Delayed-Enhancement Cardiac MRI (arxiv)
0.8786
0.7124
0.7851
1st Place in MICCAI 2020
20201008
Jun Ma
Cascaded Framework for Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI (arxiv)
0.8628
0.6224
0.7776
2nd Place in MICCAI 2020
20201008
Xue Feng
Automatic Scar Segmentation from DE-MRI Using 2D Dilated UNet with Rotation-based Augmentation (paper)
0.8356
0.4568
0.7222
3rd Place in MICCAI 2020
Metrics: DSC
Date
First Author
Title
DSC
MHD
VS
Remark
20201008
Jun Ma
Loss Ensembles for Intracranial Aneurysm Segmentation: An Embarrassingly Simple Method (Code)
0.41
8.96
0.50
1st Place in MICCAI 2020
20201008
Yuexiang Li
Automatic Aneurysm Segmentation via 3D U-Net Ensemble
0.40
8.67
0.48
2nd Place in MICCAI 2020
20201008
Riccardo De Feo
Multi-loss CNN ensemblesfor aneurysm segmentation
0.28
18.13
0.39
3rd Place in MICCAI 2020
Multi-Centre, Multi-Vendor & Multi-Disease Cardiac Image Segmentation Challenge (M&Ms) (Results)
Date
First Author
Title
LV
MYO
RV
Remark
20201004
Peter Full
The effect of Data Augmentation on Robustness against Domain Shifts in cMRI Segmentation
0.910
0.849
0.884
1st Place in MICCAI 2020
20201004
Yao Zhang
Semi-Supervised Cardiac Image Segmentation via Label Propagation and Style Transfer
0.906
0.840
0.878
2nd Place in MICCAI 2020
20201004
Jun Ma
Histogram Matching Augmentation for Domain Adaptation (code)
0.902
0.835
0.874
3rd Place in MICCAI 2020
Dice values are reported. Video records are available on pathable . All the papers are in press
Date
First Author
Title
DSC
Remark
20201004
Andrei Iantsen
Squeeze-and-Excitation Normalization for Automated Delineation of Head and Neck Primary Tumors in Combined PET and CT Images (paper)
0.759
1st Place in MICCAI 2020
20201004
Jun Ma
Combining CNN and Hybrid Active Contours for Head and Neck Tumor Segmentation in CT and PET Images (paper)
0.752
2nd Place in MICCAI 2020
Date
First Author
Title
IoU
Remark
20201004
Mingyu Wang
A Simple Cascaded Framework for Automatically Segmenting Thyroid Nodules (code)
0.8254
1st Place in MICCAI 2020
20201004
Huai Chen
LRTHR-Net: A Low-Resolution-to-High-Resolution Framework to Iteratively Refine the Segmentation of Thyroid Nodule in Ultrasound Images
0.8196
2nd Place in MICCAI 2020
20201004
Zhe Tang
Coarse to Fine Ensemble Network for Thyroid Nodule Segmentation
0.8194
3rd Place in MICCAI 2020
Video records are available on pathable
2020 ICIAR: Automatic Lung Cancer Patient Management (LNDb) (LNDb)
Results
Date
First Author
Title
IoU
Remark
20200625
Alexandr G. Rassadin
Deep Residual 3D U-Net for Joint Segmentation and Texture Classification of Nodules in Lung (arxiv)
0.5221
1st Place in Seg. Task
Challenges on Open Leaderboard Phase 2019 MICCAI: Kidney Tumor Segmentation Challenge (KiTS19) Leaderboard (2019/07/30)
Date
First Author
Title
Composite Dice
Kidney Dice
Tumor Dice
202004
Fabian Isensee Automated Design of Deep Learning Methods for Biomedical Image Segmentation (arxiv)
0.9168
0.9793
0.8542
20190730
Fabian Isensee An attempt at beating the 3D U-Net (paper)
0.9123
0.9737
0.8509
20190730
Xiaoshuai Hou
Cascaded Semantic Segmentation for Kidney and Tumor (paper)
0.9064
0.9674
0.8454
20190730
Guangrui Mu
Segmentation of kidney tumor by multi-resolution VB-nets (paper)
0.9025
0.9729
0.8321
2017 ISBI & MICCAI: Liver tumor segmentation challenge (LiTS) Summary: The Liver Tumor Segmentation Benchmark (LiTS), Patrick Bilic et al. 201901 (arxiv)
Date
First Author
Title
Liver Per Case Dice
Liver Global Dice
Tumor Per Case Dice
Tumor Global Dice
202004
Fabian Isensee Automated Design of Deep Learning Methods for Biomedical Image Segmentation (arxiv)
0.967
0.970
0.763
0.858
201909
Xudong Wang Volumetric Attention for 3D Medical Image Segmentation and Detection (MICCAI2019)
-
-
0.741
-
201908
Jianpeng Zhang
Light-Weight Hybrid Convolutional Network for Liver Tumor Segmentation (IJCAI 2019)
0.965
0.968
0.730
0.820
202007
Youbao Tang
E^2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans (arXiv)
0.966
0.968
0.724
0.829
201709
Xiaomeng Li H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes, (TMI) , (Keras code)
0.961
0.965
0.722
0.824
2012 MICCAI: Prostate MR Image Segmentation (PROMISE12)
Date
First Author
Title
Whole Dice
Overall Score
201904
Anonymous
3D segmentation and 2D boundary network (paper)
-
90.34
201902
Qikui Zhu
Boundary-weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation (paper)
91.41
89.59
Recent results can be found here .
Task
Data Info
Fabian Isensee et al. (paper)
nnUNet v2 Qihang Yu et al. (paper)
Brats
Multimodal multisite MRI data (FLAIR, T1w, T1gd,T2w), (484 Training + 266 Testing)
0.68/0.48/0.68
68/46.8/68.46
67.6/48.6/69.7
Heart
Mono-modal MRI (20 Training + 10 Testing)
0.93
96.74
92.49
Hippocampus head and body
Mono-modal MRI (263 Training + 131 Testing)
0.90/0.89
90/88.69
89.37/87.96
Liver & Tumor
Portal venous phase CT (131 Training + 70 Testing)
0.95/0.74
95.75/75.97
94.98/72.89
Lung
CT (64 Training + 32 Testing)
0.69
73.97
70.44
Pancreas & Tumor
Portal venous phase CT (282 Training +139 Testing)
0.80/0.52
81.64/52.78
80.76/54.41
Prostate central gland and peripheral
Multimodal MR (T2, ADC) (32 Training + 16 Testing)
0.76/0.90
76.59/89.62
74.88/88.75
Hepatic vessel& Tumor
CT, (303 Training + 140 Testing)
0.63/0.69
66.46/71.78
64.73/71
Spleen
CT (41 Training + 20 Testing)
0.96
97.43
96.28
Colon
CT (41 Training + 20 Testing)
0.56
58.33
58.90
Only showing Dice Score.
Recent papers on Medical Segmentation Decathlon
Date
First Author
Title
Score
20181129
Yingda Xia
3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training (paper)
no test set score
20190606
Zhuotun Zhu
V-NAS: Neural Architecture Search for Volumetric Medical Image Segmentation (arxiv)
Lung tumor: 55.27; Pancreas and tumor: 79.94, 37.78 (4-fold CV)
Past Challenges (New submission closed) 2020 MICCAI-MyoPS: Myocardial pathology segmentation combining multi-sequence CMR (MyoPS 2020)
Date
First Author
Title
Scar
Scar+Edema
Remark
20201004
Shuwei Zhai
Myocardial Edema and Scar Segmentation using a Coarse-to-Fine Framework with Weighted Ensemble (paper in press)
0.672 (0.244)
0.731 (0.109)
1st Place in MICCAI 2020
2019 MICCAI: Structure Segmentation for Radiotherapy Planning (StructSeg)
Results
Date
First Author
Title
Head & Neck OAR
Head & Neck GTV
Chest OAR
Chest GTV
20191001
Huai Chen
TBD
0.8109
0.6666
0.9011
0.5406
20191001
Fabian Isensee nnU-Net
0.7988
0.6398
0.9083
0.5343
20191001
Yujin Hu
TBD
0.7956
0.6245
0.9024
0.5447
20191001
Xuechen Liu
TBD
-
-
0.9066
-
2019 MICCAI: Multi-sequence Cardiac MR Segmentation Challenge (MS-CMRSeg)
Multi-sequence ventricle and myocardium segmentation.
Date
First Author
Title
LV
Myo
RV
20190821
Chen Chen Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation (arxiv)
0.92
0.83
0.88
Date
First Author
Title
Dice
20190905
Aimoldin Anuar
SIIM-ACR Pneumothorax Challenge - 1st place solution (pytorch)
0.8679
2019 ISBI: Segmentation of THoracic Organs at Risk in CT images (SegTHOR)
Date
First Author
Title
Esophagus
Heart
Trachea
Aorta
20190320
Miaofei Han
Segmentation of CT thoracic organs by multi-resolution VB-nets (paper)
86
95
92
94
20190606
Shadab Khan Extreme Points Derived Confidence Map as a Cue For Class-Agnostic Segmentation Using Deep Neural Network (paper)
89.87
95.97
91.87
94
Challenge results
2018 MICCAI: Multimodal Brain Tumor Segmentation Challenge(BraTS) Summary: Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge Spyridon Bakas et al. 201811, (arxiv)
Rank(18)
First Author
Title
Val. WT/EN/TC Dice
Test Val. WT/ET/TC Dice
1
Andriy Myronenko
3D MRI Brain Tumor Segmentation Using Autoencoder Regularization (paper)
0.91/0.823/0.867
0.884/0.766/0.815
2
Fabian Isensee No New-Net (paper)
0.913/0.809/0.863
0.878/0.779/0.806
3
Richard McKinley Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor Segmentation (paper)
0.903/0.796/0.847
0.886/0.732/0.799
3
Chenhong Zhou
Learning Contextual and Attentive Information for Brain Tumor Segmentation (paper)
0.9095/0.8136/0.8651
0.8842/0.7775/0.7960
New
Xuhua Ren Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation (paper)
0.915/0.832/0.883
-
2018 MICCAI: Ischemic stroke lesion segmentation (ISLES )
Date
First Author
Title
Dice
20190605
Yu Chen
OctopusNet: A Deep Learning Segmentation Network for Multi-modal Medical Images (paper)
57.90 (5-fold CV)
201812
Hoel Kervadec Boundary loss for highly unbalanced segmentation (paper) , (pytorch 1.0 code)
65.6
201809
Tao Song
3D Multi-scale U-Net with Atrous Convolution for Ischemic Stroke Lesion Segmentation, (paper)
55.86
201809
Pengbo Liu
Stroke Lesion Segmentation with 2D Convolutional Neutral Network and Novel Loss Function, (paper)
55.23
201809
Yu Chen
Ensembles of Modalities Fused Model for Ischemic Stroke Lesion Segmentation, (paper)
-
2018 MICCAI Grand Challenge on MR Brain Image Segmentation (MRBrainS18)
Eight Label Segmentation Results (201809)
Rank
First Author
Title
Score
1
Miguel Luna
3D Patchwise U-Net with Transition Layers for MR Brain Segmentation (paper)
9.971
2
Alireza Mehrtash
U-Net with various input combinations (paper)
9.915
3
Xuhua Ren
Ensembles of Multiple Scales, Losses and Models for Segmentation of Brain Area (paper)
9.872
201906
Xuhua Ren Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization (arxiv )
5 fold CV Dice: 84.46
Three Label Segmentation Results (201809)
Rank
First Author
Title
GM/WM/CSF Dice
Score
1
Liyan Sun
Brain Tissue Segmentation Using 3D FCN with Multi-modality Spatial Attention (paper)
0.86/0.889/0.850
11.272
2018 MICCAI: Left Ventricle Full Quantification Challenge (LVQuan18)
Rank
First Author
Title
1
Jiahui Li
Left Ventricle Full Quantification Using Deep Layer Aggregation Based Multitask Relationship Learning, (paper)
2
Eric Kerfoot Left-Ventricle Quantification Using Residual U-Net, (paper)
3
Fumin Guo Cardiac MRI Left Ventricle Segmentation and Quantification: A Framework Combining U-Net and Continuous Max-Flow (paper)
2018 MICCAI: Atrial Segmentation Challenge (AtriaSeg)
Rank
First Author
Title
Score
1
Qing Xia
Automatic 3D Atrial Segmentation from GE-MRIs Using Volumetric Fully Convolutional Networks (paper)
0.932
2
Cheng Bian
Pyramid Network with Online Hard Example Mining for Accurate Left Atrium Segmentation (paper)
0.926
2
Sulaiman Vesal Dilated Convolutions in Neural Networks for Left Atrial Segmentation in 3D Gadolinium Enhanced-MR (paper)
0.926
Awesome Open Source Tools
Task
First Author
Title
Notes
Detection&Segmentation
Paul F. Jaeger Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection, (paper) , (code)
pytorch
Medical Image Analysis
Many excellent contributors
MONAI: M edical O pen N etwork for AI (code)
pytorch
Segmentation
Christian S. Perone MedicalTorch pytorch
Segmentation
Fabian Isensee nnU-Net (paper) (code)
pytorch
MedImgIO
Fernando Pérez García TorchIO: tools for loading, augmenting and writing 3D medical images on PyTorch (code)
pytorch
Segmentation
DLinRadiology MegSeg: a free segmentation tool for radiological images (CT and MRI)
homepage
Segmentation
Adaloglou Nikolaos
A 3D multi-modal medical image segmentation library in PyTorch (code)
pytorch
Contributions are most welcome!
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