Back
Full-text
Journal article

Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure.

  • Commowick O VISAGES: INSERM U1228 - CNRS UMR6074 - Inria, University of Rennes I, Rennes, France. Olivier.Commowick@inria.fr.
  • Istace A Department of Radiology, Lyon Sud Hospital, Hospices Civils de Lyon, Lyon, France.
  • Kain M VISAGES: INSERM U1228 - CNRS UMR6074 - Inria, University of Rennes I, Rennes, France.
  • Laurent B LaTIM, INSERM, UMR 1101, University of Brest, IBSAM, Brest, France.
  • Leray F VISAGES: INSERM U1228 - CNRS UMR6074 - Inria, University of Rennes I, Rennes, France.
  • Simon M VISAGES: INSERM U1228 - CNRS UMR6074 - Inria, University of Rennes I, Rennes, France.
  • Pop SC Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, Lyon, France.
  • Girard P Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, Lyon, France.
  • Améli R Department of Radiology, Lyon Sud Hospital, Hospices Civils de Lyon, Lyon, France.
  • Ferré JC VISAGES: INSERM U1228 - CNRS UMR6074 - Inria, University of Rennes I, Rennes, France.
  • Kerbrat A VISAGES: INSERM U1228 - CNRS UMR6074 - Inria, University of Rennes I, Rennes, France.
  • Tourdias T CHU de Bordeaux, Service de Neuro-Imagerie, Bordeaux, France.
  • Cervenansky F Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, Lyon, France.
  • Glatard T Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada.
  • Beaumont J VISAGES: INSERM U1228 - CNRS UMR6074 - Inria, University of Rennes I, Rennes, France.
  • Doyle S Pixyl Medical, Grenoble, France.
  • Forbes F Pixyl Medical, Grenoble, France.
  • Knight J Image Analysis in Medicine Lab, School of Engineering, University of Guelph, Guelph, Canada.
  • Khademi A Image Analysis in Medicine Lab (IAMLAB), Ryerson University, Toronto, Canada.
  • Mahbod A School of Technology and Health, KTH Royal Institute of Technology, Stockholm, Sweden.
  • Wang C School of Technology and Health, KTH Royal Institute of Technology, Stockholm, Sweden.
  • McKinley R Department of Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland.
  • Wagner F Department of Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland.
  • Muschelli J Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Sweeney E Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Roura E Research institute of Computer Vision and Robotics (VICOROB), University of Girona, Girona, Spain.
  • Lladó X Research institute of Computer Vision and Robotics (VICOROB), University of Girona, Girona, Spain.
  • Santos MM Centro de Informática, Universidade Federal de Pernambuco, Pernambuco, Brazil.
  • Santos WP Depto. de Eng. Biomédica, Universidade Federal de Pernambuco, Pernambuco, Brazil.
  • Silva-Filho AG Centro de Informática, Universidade Federal de Pernambuco, Pernambuco, Brazil.
  • Tomas-Fernandez X Computational Radiology Laboratory, Department of Radiology, Children's Hospital, 300 Longwood Avenue, Boston, MA, USA.
  • Urien H LTCI, Télécom ParisTech, Université Paris-Saclay, Paris, France.
  • Bloch I LTCI, Télécom ParisTech, Université Paris-Saclay, Paris, France.
  • Valverde S Research institute of Computer Vision and Robotics (VICOROB), University of Girona, Girona, Spain.
  • Cabezas M Research institute of Computer Vision and Robotics (VICOROB), University of Girona, Girona, Spain.
  • Vera-Olmos FJ Medical Image Analysis Lab, Universidad Rey Juan Carlos, Madrid, Spain.
  • Malpica N Medical Image Analysis Lab, Universidad Rey Juan Carlos, Madrid, Spain.
  • Guttmann C Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
  • Vukusic S Department of Radiology, Lyon Sud Hospital, Hospices Civils de Lyon, Lyon, France.
  • Edan G VISAGES: INSERM U1228 - CNRS UMR6074 - Inria, University of Rennes I, Rennes, France.
  • Dojat M Inserm U1216, University Grenoble Alpes, CHU Grenoble, GIN, Grenoble, France.
  • Styner M Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA.
  • Warfield SK Computational Radiology Laboratory, Department of Radiology, Children's Hospital, 300 Longwood Avenue, Boston, MA, USA.
  • Cotton F Department of Radiology, Lyon Sud Hospital, Hospices Civils de Lyon, Lyon, France.
  • Barillot C VISAGES: INSERM U1228 - CNRS UMR6074 - Inria, University of Rennes I, Rennes, France.
Show more…
  • 2018-09-14
Published in:
  • Scientific reports. - 2018
Algorithms
Female
Humans
Image Interpretation, Computer-Assisted
Image Processing, Computer-Assisted
Machine Learning
Magnetic Resonance Imaging
Male
Multiple Sclerosis
Neural Networks, Computer
Parenchymal Tissue
Retrospective Studies
English We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and independent evaluation of a large range of algorithms in a fair and completely automatic manner. This computing infrastructure was used to evaluate thirteen methods of MS lesions segmentation, exploring a broad range of state-of-theart algorithms, against a high-quality database of 53 MS cases coming from four centers following a common definition of the acquisition protocol. Each case was annotated manually by an unprecedented number of seven different experts. Results of the challenge highlighted that automatic algorithms, including the recent machine learning methods (random forests, deep learning, …), are still trailing human expertise on both detection and delineation criteria. In addition, we demonstrate that computing a statistically robust consensus of the algorithms performs closer to human expertise on one score (segmentation) although still trailing on detection scores.
Language
  • English
Open access status
gold
Identifiers
Persistent URL
https://folia.unifr.ch/global/documents/247262
Statistics
Document views: 27 File downloads:
  • Full-text: 0