Results
Leaderboard
Team | Ranking | VS_Dice | VS_ASSD | Cochlea_Dice | Cochlea_ASSD |
---|---|---|---|---|---|
Samoyed | 1 | 0.8297 | 0.5232 | 0.8488 | 0.3424 |
PKU_BIALAB | 2 | 0.8707 | 0.3660 | 0.7978 | 0.2955 |
jwc-rad | 3 | 0.8288 | 1.0436 | 0.8217 | 0.2858 |
MIP | 4 | 0.7995 | 1.2902 | 0.8248 | 0.1822 |
PremiLab | 5 | 0.7727 | 2.7762 | 0.7967 | 0.2936 |
Epione-Liryc | 6 | 0.7860 | 2.0568 | 0.7658 | 0.3858 |
MedICL | 7 | 0.7756 | 3.0634 | 0.7445 | 0.5333 |
DBMI_pitt | 8 | 0.4734 | 10.9950 | 0.7969 | 0.5086 |
Hi-Lib | 9 | 0.6686 | 4.3944 | 0.6649 | 1.2663 |
smriti161096 | 10 | 0.7230 | 2.9876 | 0.5131 | 0.9523 |
IMI | 11 | 0.6004 | 4.4732 | 0.4281 | 9.8191 |
GapMIND | 12 | 0.6081 | 3.8377 | 0.5176 | 1.6570 |
gabybaldeon | 13 | 0.6232 | 7.5786 | 0.3987 | 3.9180 |
SEU_Chen | 14 | 0.1142 | 38.0744 | 0.4945 | 14.0109 |
skjp | 15 | 0.2104 | 24.4830 | 0.2139 | 15.6275 |
IRA | 16 | 0.1193 | 30.8389 | 0.2142 | 19.5226 |
Event recording
Presentation
Proposed approaches
#1 - Samoyed
Self-Training Based Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation
Hyungseob Shin ; Hyeon Gyu Kim; Sewon Kim; Yohan Jun ; Taejoon Eo ; Dosik Hwang (Yonsei University)
#2 - PKU_BIALAB
Unsupervised Domain Adaptation in Semantic Segmentation Based on Pixel Alignment and Self-Training (PAST)
Hexin Dong; Fei Yu; Jie Zhao; Bin Dong; Li Zhang (Peking University)
#3 - jwc-rad
Using Out-of-the-Box Frameworks for Unpaired Image Translation and Image Segmentation for the crossMoDA Challenge
Jae Won Choi (College of Medicine, Seoul National University)
#4 - MIP
Cross-Modality Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation
Han Liu; Yubo Fan; Can Cui; Dingjie Su; Andrew Mcneil; Benoit Dawant (Vanderbilt University)
#5 - PremiLab
DAR-UNet: Dual Attention ResU-Net for CrossMoDa Challenge
Kai Yao; Zixian Su; Xi Yang; Kaizhu Huang; jie Sun (Xi’an Jiaotong-Liverpool University )
#6 - Epione-Liryc
Cross-Modality Domain Adaptation for Vestibular Schwannoma and cochlea segmentation from high-resolution T2 MRI (Epione-Liryc team)
Buntheng Ly; Victoriya Kashtanova; Yingyu Yang; Aurelien Maillot; Marta Nunez-Garcia; Maxime Sermesant (INRIA)
#7 - MedICL
Unsupervised Cross-modality Domain Adaptation for Segmentating Vestibular Schwannoma and Cochlea with Data Augmentation and Model Ensemble
Hao Li; Dewei Hu; Qibang Zhu; Kathleen E Larson; Huahong Zhang; Ipek Oguz
#8 - DBMI_pitt
Fast Single Direction Translation for Brain Image Domain Adaptation
Yanwu Xu; Mingming Gong ; Kayhan Batmanghelich (University of Pittsburgh - University of Melbourne)
#9 - Hi-Lib
A GANs-based Modality Fusion and Data Augmentation for CrossMoDA Challeng
Jianghao Wu; Ran Gu; Shuwei Zhai; Wenhui Lei; Guotai Wang (University of Electronic Science and Technology of China)
#10 - smriti161096
nn-Unet Training on CycleGAN-translated images for cross-modal domain adaptation in biomedical imaging
Smriti Joshi; Richard Osuala; Carlos Martın-Isla; Victor M. Campello; Carla Sendra-Balcells; Karim Lekadir; Sergio Escalera (University of Barcelona)
#11 - IMI
MIND THE domain GAP: unsupervised modality independent deformable domain
Lasse Hansen; Mattias Heinrich (University of Luebeck)
#12 - GapMIND
Learning on MIND features and noisy labels from image registration
Christian N Kruse; Mattias Heinrich (University of Luebeck)
#13 - gabybaldeon
C-MADA: Unsupervised Cross-Modality Adversarial Domain Adaptation framework for medical Image Segmentation
Maria Baldeon Calisto; Susana K. Lai-Yuen (Universidad San Francisco de Quito, University of South Florida)
#14 - SEU_chen
A Cascade nnUNet By Mini-Entropy Domain Adaptation On Segmentation of Tumor and Cochlea
Chen Xiaofei (Southeast University)
#15 - skjp
MIND THE domain GAP: unsupervised modality independent deformable domain
Satoshi Kondo (Muroran Institute of Technology)
#16 - IRA
Comparing Unsupervised Domain Adaptation and Style-Transfer Methods in CrossMoDA Challenge
Arseniy Belkov; Boris Shirokikh ; Mikhail Belyaev (Moscow Institute of Physics and Technology, Skolkovo Institute of Science and Technology)