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The evaluation framework will be launched during the 3D Cardiovascular Imaging: a MICCAI segmentation challenge workshop that will be organized during the 15th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), which will be held on October 1st, 2012 in Nice Sophia Antipolis, Côte d'Azur, France.
|Training data ready for download||March, 19th 2012|
|Testing1 data ready for download
Open for submissions
|June, 4th 2012|
Testing results and (max.) 8-page paper describing the method
|June, 4th 2012 to
June, 29th 2012
|Notification of acceptance to participants||July, 6th 2012|
|Deadline for revised manuscript (if any)||July, 27th 2012|
|On-site Testing2 data ready for download
|October, 1st 2012|
The workshop will start with the presentation and distribution of the onsite testing datasets and the start of the challenge. For the remainder of the morning session, participants will run their algorithms on this data and concurrently a poster session will take place. The organizers will evaluate the results with reference data during the lunch break. After lunch, we intend an invited lecture and a set of selected talks (based on the pre-workshop results). Following these presentations, we will have a poster session, where the participants can explain their algorithm, possibly including on-site demos. The afternoon session will conclude with a presentation of the challenge results, and a town hall discussion of maximally 1 hour.
|Morning||9.00 - 12.30||Presentation and distribution of the on-site testing datasets|
|On-site challenge: participants will run their algorithms on this data|
|Include a coffee break (10.30 - 11.00)|
|Lunch||12.30 - 14.00||Lunch break (included in the registration)|
|Concurrent poster session|
|Evaluation of the on-site challenge results by the organizers|
|Afternoon||14.00 - 15.00||Guest speaker lecture by Prof. J.C.H. Reiber (Medis, the Netherlands) "Innovations in diagnostic imaging technologies: basic principles and clinical perspectives of cardiac CTA and MRI"|
|15.00 - 15.30||Presentations from both challenges|
|15.00 - 15.15||“Automatic stenoses detection, quantification and lumen segmentation of the coronary arteries using two-point centerline extraction scheme”, Rahil Shahzad et al. (BIGR, Rotterdam, NL)|
|15.15 - 15.30||““Multi-atlas based segmentation with local label fusion for right ventricle MR images”, Wenjia Bai et al. (Imperial College London, UK)|
|15.30 - 16.00||Coffee break
Concurrent poster session
The participants can explain their algorithm and possibly include on-site demos
|16.00 - 16.30||Presentations from both challenges|
|16.00 - 16.15||“Accurate stenosis detection and quantification in coronary CTA”, Brian Mohr et al. (TMVSE, Edinburgh, UK)|
|16.15 - 16.30||“Automatic right ventricle segmentation using multi-label fusion in cardiac MRI”, Maria A. Zuluaga et al. (University College London, UK)|
|16.30 - 17.30||Presentation of the challenge results
“A Simple and Fully Automatic Right Ventricle Segmentation Method for 4-Dimensional Cardiac MR Images”,
Ching-Wei Wang, Chun-Wei Peng, and Hsiang-Chou Chen,
Graduate institute of biomedical engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.
“Right-Ventricle Segmentation with 4D Region-Merging Graph Cuts in MR”,
Oskar Maier, Daniel Jimenez Carretero, Andres Santos Lleo, and Mara J Ledesma-Carbayo,
Escuela Tecnica Superior de Ingenieros de Telecomunicacion, Universidad Politecnica de Madrid, Madrid, Spain.
“Multi-Atlas Based Segmentation with Local Label Fusion for Right Ventricle MR Images”,
Wenjia Bai, Wenzhe Shi, Haiyan Wang, Nicholas S. Peters, and Daniel Rueckert,
Biomedical Image Analysis Group, Department of Computing, Imperial College London, UK & National Heart and Lung Institute, St Mary's Hospital, Imperial College London, UK.
“Automatic Right Ventricle Segmentation using Multi-Label Fusion in Cardiac MRI”,
Maria A. Zuluaga, M. Jorge Cardoso, and Sebastien Ourselin,
Centre of Medical Image Computing University College London, London UK.
“Right ventricle segmentation by graph cut with shape prior”,
Damien Grosgeorge, Caroline Petitjean, Su Ruan,
Université de Rouen, LITIS EA 4108, France.
“Multi-Atlas Segmentation of the Cardiac MR Right Ventricle”,
Yangming Ou, Jimit Doshi, Guray Erus, and Christos Davatzikos,
Section of Biomedical Image Analysis (SBIA), Department of Radiology, University of Pennsylvania.
“Rapid Automated 3D Endocardium Right Ventricle Segmentation in MRI via Convex Relaxation and Distribution Matching Cyrus”,
M.S. Nambakhsh, Martin Rajchl, Jing Yuan, Terry M. Peters, Ismail Ben Ayed
“Vessel Segmentation Using Implicit Model-Guided Level Sets”
Chunliang Wang, Rodrigo Moreno, and Orjan Smedby,
Center for Medical Imaging Science and Visualization (CMIV), Linköping, Sweden.
“Automatic detection, quantification and lumen segmentation of the coronary arteries using two-point centerline extraction scheme”,
Rahil Shahzad*, Theo van Walsum, Hortense Kirişli, Hui Tang, Coert Metz, Michiel Schaap, Lucas van Vliet, and Wiro Niessen,
*Quantitative Imaging Group Delft, Imaging Science and Technology, Faculty of Applied Science, Delft University of Technology, Delft, The Netherlands.
“FrenchCoast: Fast, Robust Extraction for the Nice Challenge on COronary Artery Segmentation of the Tree”,
Alexander Broersen, Pieter H. Kitslaar, Michel Frenay, and Jouke Dijkstra,
Division of Image Processing, Dept. of Radiology,Leiden University Medical Center, The Netherlands.
“Probabilistic model based evaluation of coronary artery stenosis on Computed Tomography Angiography”,
Kuo-Lung Lor and Chung-Ming Chen,
Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan.
“Quantification of Coronary Arterial Stenosis by Inflating Tubes in CT Angiographic images”,
Abouzar Eslami, Amin Aboee, Zardosht Hodaei, Mandana Javanshir Moghaddam, Stephane Carlier, Amin Katouzian, and Nassir Navab,
Technical University of Munich, Munich, Germany.
“Automatic Detection of Stenoses in Computed Tomography Angiography”,
Suheyla Cetin and Gozde Unal,
Sabanci University, Istanbul, Turkey.
“Accurate Stenosis Detection and Quantification in Coronary CTA”,
Brian Mohr, Saad Masood, Costas Plakas,
Toshiba Medical Visualization Systems, Edinburgh, UK.
“Coronary artery segmentation and stenosis quantification in CT images with use of a right generalized cylinder model”,
Leonardo Flórez-Valencia*, Maciej Orkisz, Ricardo A. Corredor Jerez, Juan S. Torres González, Esteban M. Correa Agudelo, Claire Mouton, and Marcela Hernández Hoyos,
*Pontificia Universidad Javeriana, Bogotá, Colombia.
“A Hybrid Method for Coronary Artery Stenosis Detection and Quantification”,
İlkay Öksüz,Devrim Ünay, and Kamuran Kadıpaşaoğlu,
Bahçeşehir University, Istanbul, Turkey.
“Automatic Coronary Arteries StenosesDetection in 3D CT angiography”,
Imen Melki*, Hugues Talbot, Jean Cousty, Celine Pruvot, Jerome Knoplioch, Laurent Launay, and Laurent Najman,
*Universite Paris-Est, Laboratoire d'Informatique Gaspard-Monge, Equipe A3SI, Noisy-le-Grand, France.
“Coronary Artery Stenoses Detection with Random Forest”,
Matthieu Duval, Elodie Ouzeau, Frederic Precioso, and Bogdan Matuszewski,
Polytech'Nice-Sophia, Nice, France.
This year, the workshop organizers are honored to welcome Prof. J.H.C. Reiber, a world class expert capable of providing deep insight into the latest developments in cardiac CTA and MRI.
Johan H.C. Reiber received his M.Sc. EE-degree from the Delft University of Technology in 1971 and his M.Sc and Ph.D. from Stanford University, USA in 1975 and 1976, respectively.
He is (co)-author of more than 625 scientific papers, and co-author/editor of 15 books. He is editor-in-chief of the International Journal of Cardiovascular Imaging, and serves on the Editorial Board of several other journals. In 2004 he became an IEEE Fellow for his contributions to medical image analysis and its applications. Other fellowships include those of the European Society of Cardiology (1988) and the American College of Cardiology (2010).
He is also co-founder and CEO of Medis medical imaging systems BV in Leiden, a global provider of software packages for the quantitative analysis of medical images, in particular of the cardiovascular system.