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A New Automatic Cancer Colony Forming Units Counting Method

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dc.creatorRoldán N.spa
dc.creatorRodriguez L.spa
dc.creatorHernandez A.spa
dc.creatorCepeda K.spa
dc.creatorOndo Méndez, Alejandro Oyonospa
dc.creatorCancino Suárez S.L.spa
dc.creatorForero M.G.spa
dc.creatorLopéz J.M.spa
dc.date.accessioned2020-05-25T23:56:49Z
dc.date.available2020-05-25T23:56:49Z
dc.date.created2019spa
dc.description.abstractClonogenic assays are an essential tool to evaluate the survival of cancer cells that have been exposed to a certain dose of radiation. Its result can be used in the generation of strategies for the optimization of radiotherapy treatments. The analysis of this type of data requires that the specialist performs the manual counting of colony forming units (CFU), i.e., find every cell that retains the ability to produce a large progeny. This task is time consuming, prone to errors and the results are not reproducible due to specialist subjective assessment. Digital image processing tools can deal with the flaws described above. This article presents a new technique for automatic CFU counting. The proposed technique extracts the regions of interest (ROIs), where a local segmentation algorithm finds and labels the CFUs in order to quantify them. Results show good sensitivity and specificity performance compared to state-of-the-art software used for CFU detection and counting. © 2019, Springer Nature Switzerland AG.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1007/978-3-030-31321-0_40
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/22529
dc.language.isoengspa
dc.publisherSpringerspa
dc.relation.citationEndPage472
dc.relation.citationStartPage465
dc.relation.citationTitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.citationVolumeVol. 11868 LNCS
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol.11868 LNCS,(2019); pp. 465-472spa
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85076116691&doi=10.1007%2f978-3-030-31321-0_40&partnerID=40&md5=472a49850fd7b5b0b1aecf2ab4550dfdspa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subject.keywordCell proliferationspa
dc.subject.keywordCellsspa
dc.subject.keywordCytologyspa
dc.subject.keywordDiseasesspa
dc.subject.keywordImage segmentationspa
dc.subject.keywordPattern recognitionspa
dc.subject.keywordRadiotherapyspa
dc.subject.keywordCancerspa
dc.subject.keywordCell countingspa
dc.subject.keywordColony countingspa
dc.subject.keywordColony forming unitsspa
dc.subject.keywordRadiotherapy treatmentspa
dc.subject.keywordSegmentation algorithmsspa
dc.subject.keywordSensitivity and specificityspa
dc.subject.keywordSubjective assessmentsspa
dc.subject.keywordImage analysisspa
dc.subject.keywordCancerspa
dc.subject.keywordCell countingspa
dc.subject.keywordCell proliferationspa
dc.subject.keywordCFUspa
dc.subject.keywordColony countingspa
dc.subject.keywordImage analysisspa
dc.titleA New Automatic Cancer Colony Forming Units Counting Methodspa
dc.typeconferenceObjecteng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaDocumento de conferenciaspa
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