Title :
Liver segmentation for hepatic lesions detection and characterisation
Author :
Platero, C. ; Poncela, J.M. ; Gonzalez, P. ; Tobar, M.C. ; Sanguino, J. ; Asensio, G. ; Santos, E.
Author_Institution :
Appl. Bioeng. Group, Univ. Politec. de Madrid, Madrid
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.
Keywords :
edge detection; image segmentation; liver; medical image processing; patient diagnosis; 3D anisotropic diffusion processing; active contour evolution; clinical diagnosis; edge detection; hepatic lesions detection; hepatic magnetic resonance; histogram analysis; liver segmentation; morphological post processing; therapeutic response; Active contours; Anisotropic magnetoresistance; Automatic control; Histograms; Image edge detection; Image segmentation; Lesions; Liver; Magnetic resonance; Process control; Liver segmentation; active contours; anisotropic diffusion;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-2002-5
Electronic_ISBN :
978-1-4244-2003-2
DOI :
10.1109/ISBI.2008.4540920