These are raters who participated in the STACOM 2011 LV Segmentation Challenge. They have submitted their segmentation results, which were used to build the initial consensus (see [Suinesiaputra et al., 2014]).

  • AU - Manually guide-point modeling assisted fitting of cardiac model

    This is an expert-guided segmentation method where a finite element model of the LV was fitted interactively throughout the cardiac frames. It was developed by the University of Auckland, New Zealand. See [Li et al. 2010, Young et al., 2000] for more information about this method.
  • AO - Contour-constrained optical flow tracking

    This method involves manual drawing at the first frame before automatically tracks contour in the subsequent frames by minimizing energy functionals, which consist of optical flow and contour properties constraints [Fahmy et al., 2012]. This algorithm was submitted by the Nile University, Cairo, Egypt group during the 2011 LV Segmentation Challenge.
  • DS_snapshot

    DS - Block matching algorithm

    This method also involves manual drawing at the first frame and the subsequent myocardial contours were detected by using the block-matching technique [Ourselin et al., 2000]. This algorithm was submitted by Diagnostic Inc. during the 2011 LV Segmentation Challenge.
  • INR_snapshot

    INR - Layered spatio-temporal forests algorithm

    The INRIA group in France submitted an algorithm to segment myocardium based on two layers of spatio-temporal decision forests with almost no assumptions on the data nor explicitly specifying the segmentation rules [Margeta et al., 2012]. 4D spatio-temporal features to classification with decision forests were introduced in the first layer for context aware MR intensity standardization and image alignment. The second layer was then used for the final image segmentation. This is a fully automated segmentation algorithm without any user intervention.
  • SCR_snapshot

    SCR - Deformable registration method

    This fully automated method was submitted by Siemens Corporation Research group, in which they have developed an algorithm to register and to segment cardiac MR images without any user intervention. The method is based on inverse consistency of deformable registration to register all frames to the first frame [Jolly et al., 2012]. The segmentation was applied to any frame and propagated to any other frames in the sequence through forward and backward deformation fields.

Registered raters

The following list contains active participating raters and their status of submission:
Name Institution Submission status
Huafei Hu University of Sheffield, UK submitted
Tan Li Kuo University of Malaya, Kuala Lumpur submitted
Phi Vu Tran Booz Allen Hamilton, USA submitted (2 versions)
Sharath Gopal University of California, Los Angeles, USA submitted
Oliver Moolan-Feroze Bristol University, UK submitted
Kumaradevan Punithakumar University of Alberta, Canada not yet
Mahapatra Dwarikanath ETH Zurich, Switzerland not yet
Angélica Atehortúa Universidad Nacional, Bogota, Colombia not yet
Mahdi Hajiaghayi University of California, Irvine, USA unreachable
Bogdan Budescu Transilvania University, Brasov, Romania not yet
Zhijie Wang Western University, Ontario, Canada not yet
Xiahai Zhuang Shanghai Advanced Research Institute, China not yet
Yang Yu Rutgers University, USA not yet
Moslem Avendi UC Irvine, USA not yet
Lichao Wang TU Munich, German not yet
Cristian Linte Rochester Institute of Technology, USA not yet
Wenjun Tan Northeastern University, China not yet
Martin Rajchi Imperial College London, UK not yet
Wendeson da Silva Oliveira Federal University of Pernambuco, Brazil not yet
Joyce Teixeira Federal University of Pernambuco, Brazil not yet
Piere-Marc Jodoin University of Sherbrooke, Canada not yet
Gongning Luo Harbin Institute of Technology, China not yet
Yurun Ma Lanzhou University, China not yet
Maimoona Khan National University of Sciences and Technology, Pakistan not yet
Yang Xulei Institute of High Performance Computing, A*STAR, Singapore not yet
Heran Yang Xi'an Jiaotong University, China not yet
Gustavo Canavaci Barizon University of Säo Paolo, Brazil not yet
Ariel Hernán Curiale Universidad Nacional de Cuyo, Argentina not yet
Fan Yang Guizhou Medical University, China not yet
Brian Rice NeoSoft Medical, USA not yet
Hassan Mohy-ud-Din Yale University, USA not yet
Liset Romaguera Universidad Federal Do Amazonas, Brazil not yet
Aliasghar Mortazi University of Central Florida, USA not yet
Nasrin Bastani Isfahan University of Medical Science, Iran not yet
Shehzaad Dhuliawala University of Massachusetts, USA September 2017
Mobarakol Islam National University of Singapore February 2017
Mo Yuanhan Imperial College London, UK End of 2017
Mahendra Khened Indian Institute of Technology, Madras, India Oct 2017
Awais Muhammad Lodhi University of Central Punjab, Pakistan Nov 2017
Lv Xuyang Northeastern University, China Aug 2017
Manuel Morales MIT, USA Sep 2017
Defeng Chen Capital Normal University, China Sep 2017
Mohit Pandey Cornell University, USA July 2018
Xiaoming Liu Wuhan University of Science and Technology, China -