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Automatic quantification of histological studies in allergic asthma

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dc.affiliation.dptoUC3M. Departamento de Bioingenieríaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Biomedical Imaging and Instrumentation Groupes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: BSEL - Laboratorio de Ciencia e Ingeniería Biomédicaes
dc.contributor.authorAbella García, Mónica
dc.contributor.authorZubeldia, José Manuel
dc.contributor.authorConejero, Laura
dc.contributor.authorMalpica, Norberto
dc.contributor.authorVaquero López, Juan José
dc.contributor.authorDesco Menéndez, Manuel
dc.date.accessioned2011-08-19T10:28:25Z
dc.date.available2011-08-19T10:28:25Z
dc.date.issued2009
dc.description.abstractThe evaluation of new therapies to treat allergic asthma makes frequent use of histological studies. Some of them are based on microscope observation of stained paraffin lung sections to quantify cellular infiltrate, an effect directly related to allergic processes. Currently, there is no software tool available for doing this quantification automatically. This paper presents a methodology and a software tool for the quantification of cellular infiltrate in lung tissue images in an allergic asthma mouse model. The image is divided into regions of equal size, which are then classified by means of a segmentation algo rithm based on texture analysis. The classification uses three discriminant functions, built from parameters derived from the histogram and the co occurrence matrix. These functions were calculated by means of a stepwise discriminant analysis on 79 samples from a training set. Results provided a correct classification of 96.8% on an independ ent test set of 251 samples labeled manually. Regression analysis showed a good agree ment between automatic and manual methods. A reliable and easy to implement method has been developed to provide an automatic method for quantifying micros copy images of lung histological studies. Results showed similar accuracy to that pro vided by an expert, while allowing analyzing a much larger number of fields in a repea table way
dc.description.sponsorshipContract grant sponsor: CD TEAM project, CENIT program, Ministerio de Industria
dc.description.statusPublicado
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationCytometry Part A, 2009, vol. 75A, n. 3, p. 271-277
dc.identifier.doi10.1002/cyto.a.20648
dc.identifier.issn1552-4922 (print version)
dc.identifier.issn1552-4930 (electronic version)
dc.identifier.publicationfirstpage271
dc.identifier.publicationissue3
dc.identifier.publicationlastpage277
dc.identifier.publicationtitleCytometry Part A
dc.identifier.publicationvolume75A
dc.identifier.urihttps://hdl.handle.net/10016/12024
dc.language.isoeng
dc.publisherInternational Society for Advancement of Cytometry
dc.relation.publisherversionhttp://dx.doi.org/10.1002/cyto.a.20648
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaBiología y Biomedicina
dc.subject.otherMicroscopy
dc.subject.otherLung tissue
dc.subject.otherAllergic asthma
dc.subject.otherCo occurrence matrix
dc.subject.otherImage analysis
dc.subject.otherSegmentation
dc.subject.otherTexture
dc.titleAutomatic quantification of histological studies in allergic asthma
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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