dc.creatorSilvetti, Andrea
dc.creatorDelrieux, Claudio
dc.date2010
dc.date2010
dc.date2023-05-10T14:57:33Z
dc.date.accessioned2023-07-15T10:24:39Z
dc.date.available2023-07-15T10:24:39Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/152717
dc.identifierhttp://39jaiio.sadio.org.ar/sites/default/files/39-jaiio-ast-05.pdf
dc.identifierissn:1850-2806
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7491764
dc.descriptionAutomatic segmentation of different types of tissue from medical images of several sensing modalities is of great importance for clinical and research applications. In this paper, we propose a segmentation methodology based on a multifractal approach. We present different alternatives for estimating local fractal exponents in these images, as well as their global distributions –the multifractal sperctrum. We generate new images by means of grayscale mapping of these local an global computed values. The obtained results are quite promising as a tissue differentiation tool, and therefore are suitable to carry out automatic segmentation of abnormalities in medical images.
dc.descriptionSociedad Argentina de Informática e Investigación Operativa
dc.formatapplication/pdf
dc.format1575-1581
dc.languagees
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.subjectCiencias Informáticas
dc.subjectMedical Imaging
dc.subjectImage Segmentation
dc.subjectHölder Exponent
dc.subjectMultifractals
dc.titleMultifractal Analysis of Medical Images
dc.typeObjeto de conferencia
dc.typeObjeto de conferencia


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