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dc.contributor.authorAlférez Baquero, Edwin Santiago
dc.contributor.authorMerino, Ana
dc.contributor.authorMujica Delgado, Luis Eduardo
dc.contributor.authorRuiz Ordóñez, Magda
dc.contributor.authorBigorra, Laura
dc.contributor.authorRodellar Benedé, José
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtica Aplicada III
dc.date.accessioned2014-04-10T13:39:48Z
dc.date.created2013-12
dc.date.issued2013-12
dc.identifier.citationAlferez, E. [et al.]. Automatic classification of atypical lymphoid B cells using digital blood image processing. "International journal of laboratory hematology", Desembre 2013, p. 1-9.
dc.identifier.issn1751-5521
dc.identifier.urihttp://hdl.handle.net/2117/22609
dc.description.abstractIntroduction: There are automated systems for digital peripheral blood (PB) cell analysis, but they operate most effectively in nonpathological blood samples. The objective of this work was to design a methodology to improve the automatic classification of abnormal lymphoid cells. Methods: We analyzed 340 digital images of individual lymphoid cells from PB films obtained in the CellaVision DM96:150 chronic lymphocytic leukemia (CLL) cells, 100 hairy cell leukemia (HCL) cells, and 90 normal lymphocytes (N). We implemented the Watershed Transformation to segment the nucleus, the cytoplasm, and the peripheral cell region. We extracted 44 features and then the clustering Fuzzy C-Means (FCM) was applied in two steps for the lymphocyte classification. Results: The images were automatically clustered in three groups, one of them with 98% of the HCL cells. The set of the remaining cells was clustered again using FCM and texture features. The two new groups contained 83.3% of the N cells and 71.3% of the CLL cells, respectively. Conclusion: The approach has been able to automatically classify with high precision three types of lymphoid cells. The addition of more descriptors and other classification techniques will allow extending the classification to other classes of atypical lymphoid cells.
dc.format.extent9 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
dc.subject.otherAtypical lymphoid cells
dc.subject.otherHematological cytology
dc.subject.otherDigital image processing
dc.subject.otherAutomatic cell classification
dc.subject.otherPeripheral blood
dc.subject.otherMorphological analysis
dc.titleAutomatic classification of atypical lymphoid B cells using digital blood image processing
dc.typeArticle
dc.subject.lemacSang -- Malalties -- Diagnòstic
dc.contributor.groupUniversitat Politècnica de Catalunya. CoDAlab - Control, Modelització, Identificació i Aplicacions
dc.identifier.doi10.1111/ijlh.12175
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://onlinelibrary.wiley.com/doi/10.1111/ijlh.12175/abstract
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac13021292
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorAlferez, E.; Merino, A.; Mujica, L.E.; Ruiz, M.; Bigorra, L.; Rodellar, J.
local.citation.publicationNameInternational journal of laboratory hematology
local.citation.startingPage1
local.citation.endingPage9


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