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Standardized evaluation methodology and reference database for evaluating IVUS image segmentation.
Balocco, Simone; Gatta, Carlo; Ciompi, Francesco; Wahle, Andreas; Radeva, Petia; Carlier, Stephane; Unal, Gozde; Sanidas, Elias; Mauri, Josepa; Carillo, Xavier; Kovarnik, Tomas; Wang, Ching-Wei; Chen, Hsiang-Chou; Exarchos, Themis P; Fotiadis, Dimitrios I; Destrempes, François; Cloutier, Guy; Pujol, Oriol; Alberti, Marina; Mendizabal-Ruiz, E Gerardo; Rivera, Mariano; Aksoy, Timur; Downe, Richard W; Kakadiaris, Ioannis A.
Affiliation
  • Balocco S; Computer Vision Center, Bellaterra, Spain; Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Barcelona, Spain. Electronic address: balocco.simone@gmail.com.
  • Gatta C; Computer Vision Center, Bellaterra, Spain.
  • Ciompi F; Computer Vision Center, Bellaterra, Spain; Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Barcelona, Spain.
  • Wahle A; Department of Electrical & Computer Engineering, The University of Iowa, Iowa City, USA.
  • Radeva P; Computer Vision Center, Bellaterra, Spain; Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Barcelona, Spain.
  • Carlier S; UZ Brussel, Department of Cardiology, Brussels, Belgium.
  • Unal G; Faculty of Engineering and Natural Sciences, Sabanci University, Turkey.
  • Sanidas E; Cardiovascular Research Foundation, New York, USA.
  • Mauri J; Hospital Universitari "Germans Trias i Pujol", Badalona, Spain.
  • Carillo X; Hospital Universitari "Germans Trias i Pujol", Badalona, Spain.
  • Kovarnik T; 2nd Department of Internal Medicine, Charles University, Prague, Czech Republic.
  • Wang CW; National Taiwan University of Science and Technology, Taiwan.
  • Chen HC; National Taiwan University of Science and Technology, Taiwan.
  • Exarchos TP; Institute of Molecular Biology and Biotechnology, Department of Biomedical Research, Foundation for Research and Technology Hellas, University of Ioannina, Ioannina, Greece.
  • Fotiadis DI; Institute of Molecular Biology and Biotechnology, Department of Biomedical Research, Foundation for Research and Technology Hellas, University of Ioannina, Ioannina, Greece.
  • Destrempes F; Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montreal, Canada.
  • Cloutier G; Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montreal, Canada; Department of Radiology, Radio-Oncology and Nuclear Medicine, Institute of Biomedical Engineering, University of Montreal, Montreal, Canada.
  • Pujol O; Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Barcelona, Spain.
  • Alberti M; Computer Vision Center, Bellaterra, Spain; Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Barcelona, Spain.
  • Mendizabal-Ruiz EG; Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, TX, USA.
  • Rivera M; Centro de Investigacion en Matematicas, Guanajuato, Mexico.
  • Aksoy T; Faculty of Engineering and Natural Sciences, Sabanci University, Turkey.
  • Downe RW; Department of Electrical & Computer Engineering, The University of Iowa, Iowa City, USA.
  • Kakadiaris IA; Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, TX, USA.
Comput Med Imaging Graph ; 38(2): 70-90, 2014 Mar.
Article in En | MEDLINE | ID: mdl-24012215
ABSTRACT
This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated. We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be solved.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Coronary Artery Disease / Image Interpretation, Computer-Assisted / Databases, Factual / Practice Guidelines as Topic / Ultrasonography, Interventional Type of study: Diagnostic_studies / Guideline Limits: Humans Language: En Journal: Comput Med Imaging Graph Journal subject: DIAGNOSTICO POR IMAGEM Year: 2014 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Coronary Artery Disease / Image Interpretation, Computer-Assisted / Databases, Factual / Practice Guidelines as Topic / Ultrasonography, Interventional Type of study: Diagnostic_studies / Guideline Limits: Humans Language: En Journal: Comput Med Imaging Graph Journal subject: DIAGNOSTICO POR IMAGEM Year: 2014 Document type: Article