3D Frangi-based lung vessel enhancement filter penalizing airways

Jimenez Carretero, Daniel and Santos Lleo, Andres de and Kerkstra, Sjoerd and Dewi Rudyanto, Rina and Ledesma Carbayo, María Jesús (2013). 3D Frangi-based lung vessel enhancement filter penalizing airways. In: "IEEE 10th International Symposium on Biomedical Imaging (ISBI)", 07/04/2013 - 11/04/2013, San Francisco, California, USA. pp. 926-929. https://doi.org/10.1109/ISBI.2013.6556627.

Description

Title: 3D Frangi-based lung vessel enhancement filter penalizing airways
Author/s:
  • Jimenez Carretero, Daniel
  • Santos Lleo, Andres de
  • Kerkstra, Sjoerd
  • Dewi Rudyanto, Rina
  • Ledesma Carbayo, María Jesús
Item Type: Presentation at Congress or Conference (Article)
Event Title: IEEE 10th International Symposium on Biomedical Imaging (ISBI)
Event Dates: 07/04/2013 - 11/04/2013
Event Location: San Francisco, California, USA
Title of Book: IEEE 10th International Symposium on Biomedical Imaging (ISBI)
Título de Revista/Publicación: 2013 IEEE 10TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI)
Date: 2013
ISSN: 1945-7928
Subjects:
Freetext Keywords: Segmentation, vessel, lung, filter, CT
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

This paper describes a fully automatic simultaneous lung vessel and airway enhancement filter. The approach consists of a Frangi-based multiscale vessel enhancement filtering specifically designed for lung vessel and airway detection, where arteries and veins have high contrast with respect to the lung parenchyma, and airway walls are hollow tubular structures with a non negative response using the classical Frangi's filter. The features extracted from the Hessian matrix are used to detect centerlines and approximate walls of airways, decreasing the filter response in those areas by applying a penalty function to the vesselness measure. We validate the segmentation method in 20 CT scans with different pathological states within the VESSEL12 challenge framework. Results indicate that our approach obtains good results, decreasing the number of false positives in airway walls.

More information

Item ID: 28902
DC Identifier: http://oa.upm.es/28902/
OAI Identifier: oai:oa.upm.es:28902
DOI: 10.1109/ISBI.2013.6556627
Deposited by: Memoria Investigacion
Deposited on: 29 Jun 2014 11:52
Last Modified: 22 Sep 2014 11:43
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