Automated axial right ventricle to left ventricle diameter ratio computation in computed tomography pulmonary angiography

Rodríguez López, Sara; Jiménez Carretero, Daniel; San Jose Estepar, Raul; Ledesma Carbayo, Maria Jesus; Gonzalez*, German; Kumamaru, Kanako y J. Rybicki, Frank (2015). Automated axial right ventricle to left ventricle diameter ratio computation in computed tomography pulmonary angiography. "Plos One", v. 10 (n. 5); pp.. ISSN 1932-6203. https://doi.org/10.1371/journal.pone.0127797.

Descripción

Título: Automated axial right ventricle to left ventricle diameter ratio computation in computed tomography pulmonary angiography
Autor/es:
  • Rodríguez López, Sara
  • Jiménez Carretero, Daniel
  • San Jose Estepar, Raul
  • Ledesma Carbayo, Maria Jesus
  • Gonzalez*, German
  • Kumamaru, Kanako
  • J. Rybicki, Frank
Tipo de Documento: Artículo
Título de Revista/Publicación: Plos One
Fecha: 2015
Volumen: 10
Materias:
Palabras Clave Informales: Heart Ventricle, Detection, CTPA, HOG
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Ingeniería Electrónica
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Automated medical image analysis requires methods to localize anatomic structures in the presence of normal interpatient variability, pathology, and the different protocols used to acquire images for different clinical settings. Recent advances have improved object detection in the context of natural images, but they have not been adapted to the 3D context of medical images. In this paper we present a 2.5D object detector designed to locate, without any user interaction, the left and right heart ventricles in Computed Tomography Pulmonary Angiography (CTPA) images. A 2D object detector is trained to find ventricles on axial slices. Those detections are automatically clustered according to their size and position. The cluster with highest score, representing the 3D location of the ventricle, is then selected. The proposed method is validated in 403 CTPA studies obtained in patients with clinically suspected pulmonary embolism. Both ventricles are properly detected in 94.7% of the cases. The proposed method is very generic and can be easily adapted to detect other structures in medical images.

Más información

ID de Registro: 43624
Identificador DC: http://oa.upm.es/43624/
Identificador OAI: oai:oa.upm.es:43624
Identificador DOI: 10.1371/journal.pone.0127797
URL Oficial: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0127797
Depositado por: Memoria Investigacion
Depositado el: 25 Oct 2016 18:41
Ultima Modificación: 25 Oct 2016 18:41
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