A multiphase texture-based model of active contours assisted by a convolutional neural network for automatic CT and MRI heart ventricle segmentation.

Journal: Computer methods and programs in biomedicine
Published Date: Aug 31, 2021

Abstract

BACKGROUND: Left and right ventricle automatic segmentation remains one of the more important tasks in computed aided diagnosis. Active contours have shown to be efficient for this task, however they often require user interaction to provide the initial position, which drives the tool substantially dependent on a prior knowledge and a manual process.

Authors

  • Erik Carbajal-Degante
    Posgrado en Ciencia e Ingenieria de la Computación, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico. Electronic address: eydgant@comunidad.unam.mx.
  • Steve Avendaño
    Facultad de Ciencias, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico.
  • Leonardo Ledesma
    Posgrado en Ciencia e Ingenieria de la Computación, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico.
  • Jimena Olveres
    Departamento de Procesamiento de Señales, Facultad de Ingenieria, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico.
  • Enrique Vallejo
    Departamento de Cardiologia, Centro Medico ABC, Mexico City, Mexico.
  • Boris Escalante-Ramirez
    Departamento de Procesamiento de Señales, Facultad de Ingenieria, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico. Electronic address: boris@unam.mx.

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