Main goal: To develop advanced machine learning and computer vision methods to describe and characterize tissue structures (plaque, vessel, interventional devices, etc.) in IVUS imatges.

Team: Responsable: Petia Radeva membres: Oriol Pujol, Carlo Gatta, Simone Ballocco, Francescio Ciompi, Juan Diego Gómez

Keywords: IVUS, tissue characterization, ecoc, CRF, snakes.

Summary:

Consortium: Hospital Universitari “Germans Trias i Pujol”, Boston Sci.  – USA.

Collaboration:

Contact person: Petia Radeva (petia.ivanova<at>ub.edu)

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Selected publications:

  1. Simone Balocco, Carlo Gatta, Francesco Ciompi, Andreas Wahle, Petia Radeva, Stéphane Carlier, Gözde B. Ünal,Elias Sanidas, Josepa Mauri, Xavier Carrillo, Tomas Kovarnik, Ching-Wei Wang, Hsiang-Chou Chen, Themis P. Exarchos, Dimitrios I. Fotiadis, François Destrempes, Guy Cloutier, Oriol Pujol, Marina Alberti, E. Gerardo Mendizabal-Ruiz, Mariano Rivera, Timur Aksoy, Richard W. Downe, Ioannis A. Kakadiaris: Standardized evaluation methodology and reference database for evaluating IVUS image segmentation. Comp. Med. Imag. and Graph. 38(2): 70-90 (2014)
  2. Francesco Ciompi, Oriol Pujol, Petia Radeva: ECOC-DRF: Discriminative random fields based on error correcting output codes. Pattern Recognition 47(6): 2193-2204 (2014)
  3. Francesco Ciompi, Oriol Pujol, Carlo Gatta, Marina Alberti, Simone Balocco, Xavier Carrillo, Josepa Mauri-Ferre,Petia Radeva: HoliMAb: A holistic approach for Media-Adventitia border detection in intravascular ultrasound. Medical Image Analysis 16(6): 1085-1100 (2012)

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Contact person: Petia Radeva (petia.ivanova<at>ub.edu)