Head
2019 MICCAI: Multimodal Brain Tumor Segmentation Challenge (BraTS2019) (Ongoing!!!)
2019 MICCAI: Automatic Structure Segmentation for Radiotherapy Planning Challenge (Ongoing!!!)
2018 MICCAI: Multimodal Brain Tumor Segmentation Challenge
2018 MICCAI: Ischemic stroke lesion segmentation
2018 MICCAI Grand Challenge on MR Brain Image Segmentation
Chest & Abdomen
2019 MICCAI: VerSe2019: Large Scale Vertebrae Segmentation Challenge (Ongoing!!!)
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
Awesome Open Source Tools
Loss functions for class imbalanced Problems
2019 MICCAI: Multimodal Brain Tumor Segmentation Challenge (BraTS2019) (Ongoing!!!)
2019 MICCAI: 6-month Infant Brain MRI Segmentation from Multiple Sites (iSeg2019) (Ongoing!!!)
(MS-CMRSeg) Waiting for results
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
(KiTS19) Leaderboard (2019/07/30)
Date
First Author
Title
Composite Dice
Kidney Dice
Tumor Dice
Remark
20190730
Fabian Isensee An attempt at beating the 3D U-Net (paper)
0.9123
0.9737
0.8509
1st Place
20190730
Xiaoshuai Hou
Cascaded Semantic Segmentation for Kidney and Tumor (paper)
0.9064
0.9674
0.8454
2nd Place
20190730
Guangrui Mu
Segmentation of kidney tumor by multi-resolution VB-nets (paper)
0.9025
0.9729
0.8321
3rd Place
(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
(LiTS) Summary: The Liver Tumor Segmentation Benchmark (LiTS), Patrick Bilic et al. 201901 (arxiv)
Date
First Author
Title
Liver Dice
Tumor Dice
201709
Xiaomeng Li H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes, (paper) , (Keras code)
0.961
0.722
(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
Task
Data Info
Fabian Isensee et al. (paper)
Yingda Xia et al. (paper)
Brats
Multimodal multisite MRI data (FLAIR, T1w, T1gd,T2w), (484 Training + 266 Testing)
0.68/0.48/0.68
0.675/0.45/0.68
Heart
Mono-modal MRI (20 Training + 10 Testing)
0.93
0.925
Hippocampus head and body
Mono-modal MRI (263 Training + 131 Testing)
0.90/0.89
0.88/0.867
Liver & Tumor
Portal venous phase CT (131 Training + 70 Testing)
0.95/0.74
0.95/0.714
Lung
CT (64 Training + 32 Testing)
0.69
0.52
Pancreas & Tumor
Portal venous phase CT (282 Training +139 Testing)
0.80/0.52
0.784/0.385
Prostate central gland and peripheral
Multimodal MR (T2, ADC) (32 Training + 16 Testing)
0.76/0.90
0.69/0.867
Hepatic vessel& Tumor
CT, (303 Training + 140 Testing)
0.63/0.69
-
Spleen
CT (41 Training + 20 Testing)
0.96
-
Colon
CT (41 Training + 20 Testing)
0.56
-
Only showing Dice Score.
Date
First Author
Title
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)
(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
-
(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)
-
(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
(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)
(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
Date
First Author
Title
Conference/Journal
201904
Davood Karimi
Reducing the Hausdorff Distance in Medical Image Segmentation with Convolutional Neural Networks (paper)
arxiv
201901
Seyed Raein Hashemi Asymmetric Loss Functions and Deep Densely Connected Networks for Highly Imbalanced Medical Image Segmentation: Application to Multiple Sclerosis Lesion Detection (paper) IEEE Access
201812
Hoel Kervadec Boundary loss for highly unbalanced segmentation (paper) , (pytorch 1.0 code) MIDL 2019
201810
Nabila Abraham A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation (paper)
ISBI 2019
201809
Fabian Isensee CE+Dice nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation (paper) arxiv
201808
Ken C. L. Wong 3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes (paper)
MICCAI 2018
201806
Javier Ribera Weighted Hausdorff Distance: Locating Objects Without Bounding Boxes (paper) , (pytorch code) CVPR 2019
201708
Tsung-Yi Lin Focal Loss for Dense Object Detection (paper) , (code) ICCV, TPAMI
20170711
Carole Sudre Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations (paper) DLMIA 2017
20170703
Lucas Fidon Generalised Wasserstein Dice Score for Imbalanced Multi-class Segmentation using Holistic Convolutional Networks (paper) MICCAI 2017 BrainLes
201705
Maxim Berman The Lovász-Softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks (paper) , (code)
CVPR 2018
201701
Seyed Sadegh Mohseni Salehi Tversky loss function for image segmentation using 3D fully convolutional deep networks (paper) MICCAI 2017 MLMI
201612
Md Atiqur Rahman Optimizing Intersection-Over-Union in Deep Neural Networks for Image Segmentation (paper)
2016 International Symposium on Visual Computing
201606
Fausto Milletari "Dice Loss" V-net: Fully convolutional neural networks for volumetric medical image segmentation (paper) , (caffe code) International Conference on 3D Vision
201511
Tom Brosch "Sensitivity-Specifity loss" Deep Convolutional Encoder Networks for Multiple Sclerosis Lesion Segmentation (paper) MICCAI 2015
201505
Olaf Ronneberger "Weighted cross entropy" U-Net: Convolutional Networks for Biomedical Image Segmentation (paper) MICCAI 2015
201309
Gabriela Csurka What is a good evaluation measure for semantic segmentation? (paper)
BMVA 2013
Most of the corresponding code can be found here .
Contributions are most welcome!
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