Semantic segmentation with DenseNets for carotid artery ultrasound plaque segmentation and CIMT estimation.

Journal: Artificial intelligence in medicine
PMID: 32143791

Abstract

BACKGROUND AND OBJECTIVE: The measurement of carotid intima media thickness (CIMT) in ultrasound images can be used to detect the presence of atherosclerotic plaques. Usually, the CIMT estimation strategy is semi-automatic, since it requires: (1) a manual examination of the ultrasound image for the localization of a region of interest (ROI), a fast and useful operation when only a small number of images need to be measured; and (2) an automatic delineation of the CIM region within the ROI. The existing efforts for automating the process have replicated the same two-step structure, resulting in two consecutive independent approaches. In this work, we propose a fully automatic single-step approach based on semantic segmentation that allows us to segment the plaque and to estimate the CIMT in a fast and useful manner for large data sets of images.

Authors

  • Maria Del Mar Vila
    CIBER Enfermedades Cardiovasculares, Instituto de Salud Carlos III, Monforte de Lemos 3-5, Pabellón 11, 28029 Madrid, Spain; IMIM, Institut Hospital del Mar d'Investigacions Mèdiques, Dr. Aiguader 88, 08003 Barcelona, Spain; Departament de Matemà tiques i Informà tica, Universitat de Barcelona, Gran Via de les Corts Catalanes 585, 08007 Barcelona, Spain. Electronic address: mvila@imim.es.
  • Beatriz Remeseiro
    Department of Computer Science, Universidad de Oviedo, Campus de Gijón s/n, 33203 Gijón, Spain.
  • Maria Grau
    IMIM, Institut Hospital del Mar d'Investigacions Mèdiques, Dr. Aiguader 88, 08003 Barcelona, Spain; CIBER Enfermedades Cardiovasculares, Instituto de Salud Carlos III, Monforte de Lemos 3-5, Pabellón 11, 28029 Madrid, Spain; Departament de Medicina, Universitat de Barcelona, Carrer Casanova, 143, 08036 Barcelona, Spain.
  • Roberto Elosua
    IMIM, Institut Hospital del Mar d'Investigacions Mèdiques, Dr. Aiguader 88, 08003 Barcelona, Spain; CIBER Enfermedades Cardiovasculares, Instituto de Salud Carlos III, Monforte de Lemos 3-5, Pabellón 11, 28029 Madrid, Spain; Facultat de Medicina, Universitat de Vic - Universitat Central de Catalunya, Ctra. Roda, 70, 08500 Vic, Spain.
  • Angels Betriu
  • Elvira Fernandez-Giraldez
    UDETMA i Servei Nefrologia, Hospital Universitari Arnau de Vilanova, IRB (Institut de Recerca Biomèdica de Lleida), Av. Rovira Roure, 80, 25198 Lleida, Spain.
  • Laura Igual

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