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MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans.
Mendrik, Adriënne M; Vincken, Koen L; Kuijf, Hugo J; Breeuwer, Marcel; Bouvy, Willem H; de Bresser, Jeroen; Alansary, Amir; de Bruijne, Marleen; Carass, Aaron; El-Baz, Ayman; Jog, Amod; Katyal, Ranveer; Khan, Ali R; van der Lijn, Fedde; Mahmood, Qaiser; Mukherjee, Ryan; van Opbroek, Annegreet; Paneri, Sahil; Pereira, Sérgio; Persson, Mikael; Rajchl, Martin; Sarikaya, Duygu; Smedby, Örjan; Silva, Carlos A; Vrooman, Henri A; Vyas, Saurabh; Wang, Chunliang; Zhao, Liang; Biessels, Geert Jan; Viergever, Max A.
  • Mendrik AM; Image Sciences Institute, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands.
  • Vincken KL; Image Sciences Institute, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands.
  • Kuijf HJ; Image Sciences Institute, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands.
  • Breeuwer M; Philips Healthcare, 5680 DA Best, Netherlands; Faculty of Biomedical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, Netherlands.
  • Bouvy WH; Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands.
  • de Bresser J; Department of Radiology, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands.
  • Alansary A; BioImaging Laboratory, Bioengineering Department, University of Louisville, Louisville, KY 40292, USA.
  • de Bruijne M; Biomedical Imaging Group Rotterdam, Departments of Medical Informatics and Radiology, Erasmus MC, 3015 CN Rotterdam, Netherlands; Department of Computer Science, University of Copenhagen, 2100 Copenhagen, Denmark.
  • Carass A; Image Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
  • El-Baz A; BioImaging Laboratory, Bioengineering Department, University of Louisville, Louisville, KY 40292, USA.
  • Jog A; Image Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
  • Katyal R; Department of Electronics and Communication Engineering, The LNM Institute of Information Technology, Jaipur 302031, India.
  • Khan AR; Imaging Laboratories, Robarts Research Institute, London, ON, Canada N6A 5B7; Department of Medical Biophysics, Western University, London, ON, Canada N6A 3K7.
  • van der Lijn F; Biomedical Imaging Group Rotterdam, Departments of Medical Informatics and Radiology, Erasmus MC, 3015 CN Rotterdam, Netherlands.
  • Mahmood Q; Signals and Systems, Chalmers University of Technology, 41296 Gothenburg, Sweden.
  • Mukherjee R; Applied Physics Laboratory, Johns Hopkins University, Laurel, MD 20723, USA.
  • van Opbroek A; Biomedical Imaging Group Rotterdam, Departments of Medical Informatics and Radiology, Erasmus MC, 3015 CN Rotterdam, Netherlands.
  • Paneri S; Department of Electronics and Communication Engineering, The LNM Institute of Information Technology, Jaipur 302031, India.
  • Pereira S; Department of Electronics, University of Minho, 4800-058 Guimarães, Portugal.
  • Persson M; Signals and Systems, Chalmers University of Technology, 41296 Gothenburg, Sweden.
  • Rajchl M; Imaging Laboratories, Robarts Research Institute, London, ON, Canada N6A 5B7; Department of Computing, Imperial College London, London SW7 2AZ, UK.
  • Sarikaya D; Computer Science and Engineering Department, State University of New York at Buffalo, Buffalo, NY 14260-2500, USA.
  • Smedby Ö; Center for Medical Imaging Science and Visualization, Linköping University, 58185 Linköping, Sweden; Department of Radiology and Department of Medical and Health Sciences, Linköping University, 58185 Linköping, Sweden.
  • Silva CA; Department of Electronics, University of Minho, 4800-058 Guimarães, Portugal.
  • Vrooman HA; Biomedical Imaging Group Rotterdam, Departments of Medical Informatics and Radiology, Erasmus MC, 3015 CN Rotterdam, Netherlands.
  • Vyas S; Applied Physics Laboratory, Johns Hopkins University, Laurel, MD 20723, USA.
  • Wang C; Center for Medical Imaging Science and Visualization, Linköping University, 58185 Linköping, Sweden; Department of Radiology and Department of Medical and Health Sciences, Linköping University, 58185 Linköping, Sweden.
  • Zhao L; Computer Science and Engineering Department, State University of New York at Buffalo, Buffalo, NY 14260-2500, USA.
  • Biessels GJ; Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands.
  • Viergever MA; Image Sciences Institute, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands.
Comput Intell Neurosci ; 2015: 813696, 2015.
Article en En | MEDLINE | ID: mdl-26759553
ABSTRACT
Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain MRI scans of elderly subjects (65-80 y). Participants apply their algorithms to the provided data, after which their results are evaluated and ranked. Full manual segmentations of GM, WM, and CSF are available for all scans and used as the reference standard. Five datasets are provided for training and fifteen for testing. The evaluated methods are ranked based on their overall performance to segment GM, WM, and CSF and evaluated using three evaluation metrics (Dice, H95, and AVD) and the results are published on the MRBrainS13 website. We present the results of eleven segmentation algorithms that participated in the MRBrainS13 challenge workshop at MICCAI, where the framework was launched, and three commonly used freeware packages FreeSurfer, FSL, and SPM. The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Encéfalo / Imagen por Resonancia Magnética Límite: Aged / Aged80 / Female / Humans / Male Idioma: En Año: 2015 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Search on Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Encéfalo / Imagen por Resonancia Magnética Límite: Aged / Aged80 / Female / Humans / Male Idioma: En Año: 2015 Tipo del documento: Article