Liver Segmentation for Hepatic Lesions Detection and Characterisation

Platero Dueñas, Carlos and Poncela Pardo, Jose Manuel and Gonzalez Manchon, Pedro Maria and Tobar Puente, M. del Carmen and Sanguino Botella, Fco. Javier and Asensio Madrid, Gabriel and Santos, Ernesto (2008). Liver Segmentation for Hepatic Lesions Detection and Characterisation. In: "5th IEEE International Symposium on Biomedical Imaging - From Nano to Macro, 2008", 14/05/2008-17/05/2008, Paris, Francia. ISBN 978-1-4244-2002-5. pp. 13-16.

Description

Title: Liver Segmentation for Hepatic Lesions Detection and Characterisation
Author/s:
  • Platero Dueñas, Carlos
  • Poncela Pardo, Jose Manuel
  • Gonzalez Manchon, Pedro Maria
  • Tobar Puente, M. del Carmen
  • Sanguino Botella, Fco. Javier
  • Asensio Madrid, Gabriel
  • Santos, Ernesto
Item Type: Presentation at Congress or Conference (Article)
Event Title: 5th IEEE International Symposium on Biomedical Imaging - From Nano to Macro, 2008
Event Dates: 14/05/2008-17/05/2008
Event Location: Paris, Francia
Title of Book: Proceedings of the 5th IEEE International Symposium on Biomedical Imaging - From Nano to Macro, 2008
Date: 2008
ISBN: 978-1-4244-2002-5
Subjects:
Freetext Keywords: Liver segmentation, anisotropic diffusion, active contours
Faculty: E.U.I.T. Industrial (UPM)
Department: Matemática Aplicada
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The detection and characterisation of hepatic lesions is fundamental in clinical practice, from the diagnosis stages to the evolution of the therapeutic response. Hepatic magnetic resonance is a usual practice in the localization and quantification of lesions. Automatic segmentation of the liver is illustrated in T1 weighted images. This task is necessary for detecting the lesions. The proposed liver segmentation is based on 3D anisotropic diffusion processing without any control parameter. Combinations of edge detection techniques, histogram analysis, morphological post-processing and evolution of an active contour have been applied to the liver segmentation. The active contour evolution is based on the minimization of variances in luminance between the liver and its closest neighbourhood.

More information

Item ID: 3326
DC Identifier: http://oa.upm.es/3326/
OAI Identifier: oai:oa.upm.es:3326
Official URL: http://www.biomedicalimaging.org/2008/
Deposited by: Memoria Investigacion
Deposited on: 08 Mar 2011 09:06
Last Modified: 20 Apr 2016 12:53
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