Parameter estimation in non-homogeneous boolean models: an application to plant defense response
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Otros documentos de la autoría: Gallego, María Ángeles; Ibáñez Gual, Maria Victoria; Simó, Amelia
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comunitat-uji-handle2:10234/7037
comunitat-uji-handle3:10234/8635
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Título
Parameter estimation in non-homogeneous boolean models: an application to plant defense responseFecha de publicación
2014-09xmlui.dri2xhtml.METS-1.0.item-edition
pdf de la editorialEditor
International Society for StereologyISSN
1854-5165; 1580-3139Cita bibliográfica
GALLEGO, Maria Angeles; SIM, AMELIA. PARAMETER ESTIMATION IN NON-HOMOGENEOUS BOOLEAN MODELS: AN APPLICATION TO PLANT DEFENSE RESPONSE. Image Analysis & Stereology, 2014, vol. 34, no 1, p. 27-38.Tipo de documento
info:eu-repo/semantics/articleVersión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Many medical and biological problems require to extract information from microscopical images. Boolean
models have been extensively used to analyze binary images of random clumps in many scientific fields. In
this ... [+]
Many medical and biological problems require to extract information from microscopical images. Boolean
models have been extensively used to analyze binary images of random clumps in many scientific fields. In
this paper, a particular type of Boolean model with an underlying non-stationary point process is considered.
The intensity of the underlying point process is formulated as a fixed function of the distance to a region
of interest. A method to estimate the parameters of this Boolean model is introduced, and its performance
is checked in two different settings. Firstly, a comparative study with other existent methods is done using
simulated data. Secondly, the method is applied to analyze the longleaf data set, which is a very popular data
set in the context of point processes included in the R package spatstat. Obtained results show that the new
method provides as accurate estimates as those obtained with more complex methods developed for the general
case. Finally, to illustrate the application of this model and this method, a particular type of phytopathological
images are analyzed. These images show callose depositions in leaves of Arabidopsis plants. The analysis of
callose depositions, is very popular in the phytopathological literature to quantify activity of plant immunity. [-]
Publicado en
Image Analysis & Stereology, 2014, vol. 34, no 1Derechos de acceso
The original publication is available at http://www.wise-t.com/ias
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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