Current results of CHAOS

In this page, results of the online submissions are presented for each task


Task 1: Liver Segmentation (CT-MRI)

Team Name                   Date            Score  
PKDIAv2                  07-May-2019        50.661
METU_MMLAB_v102 22-Apr-2019 42.542

Task 2: Liver Segmentation (CT only)

Team Name                   Date            Score  

PKDIAv2                  07-May-2019        82.457
Dawn 05-May-2019 75.998
DeepMedic(Post Pro.) 21-May-2019 73.317
NEHUSGGSv2 14-May-2019 65.180
DeepMedic 21-May-2019 54.328
NEHUSGGS 09-May-2019 52.701
KCliver 17-May-2019 49.220
Liver_AI_Team2 28-Apr-2019 25.304
Liver_AI_Team 22-Apr-2019 14.518


Task 3: Liver Segmentation (MRI only)

Team Name                   Date            Score  
PKDIAv2                  07-May-2019        70.712
METU_MMLAB_v102 22-Apr-2019 53.152

Task 4: Segmentation of abdominal organs (CT+MRI)

Team Name                   Date            Score  
PKDIAv2                  07-May-2019        49.634


Task 5: Segmentation of abdominal organs (MRI only)

Team Name                  Date             Score  
PKDIAv2                  07-May-2019        66.463
METU_MMLAB_v102 22-Apr-2019 56.012

Team Information

PKDIA: Pierre-Henri Conze et al. - IMT Atlantique, Brest, France

METU_MMLAB: Bora Baydar, Savaş Özkan, Gözde Bozdağı Akar, Dept. of Electrical and Electronics Eng., Middle East Technical University, Ankara, Turkey

NEHUSGGS: Gajendra Kumar Mourya et al. - Department of Biomedical Engineering, SOT, North Eastern Hill University, Shillong, Meghalaya, India

Dawn: South China University of Technology

Liver_AI_Team: D.Sabarinathan(Couger Inc, Japan), Dr. Parisa Beham, Dr. Priya Kansal (Sethu Institute of Technology, India)

KCliver: Chen Kun, Fudan University Shanghai, China

DeepMedic [Applied by organizers]: https://biomedia.doc.ic.ac.uk/software/deepmedic/ Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK

  1. Konstantinos Kamnitsas, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Daniel Rueckert, and Ben Glocker, “Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation”, Medical Image Analysis, 2016.
  2. Konstantinos Kamnitsas, Liang Chen, Christian Ledig, Daniel Rueckert, and Ben Glocker, “Multi-Scale 3D CNNs for segmentation of brain Lesions in multi-modal MRI”, in proceeding of ISLES challenge, MICCAI 2015.