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Non-Nuclei Tissue Characterization of Histopathological Images: A Processing Step to Improve Nuclei Segmentation Methods

dc.rights.licenseReconocimiento 4.0 Internacional
dc.contributor.advisorRomero Castro, Edgar Eduardo
dc.contributor.authorArias Vesga, Christian Leonardo
dc.date.accessioned2023-01-13T20:00:00Z
dc.date.available2023-01-13T20:00:00Z
dc.date.issued2022
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/82925
dc.descriptionIlustraciones, fotografías a color, imágenes, gráficas
dc.description.abstractEste estudio presenta una novedosa estrategia para caracterizar y eliminar la señal no nuclear (ruido) en las imágenes histopatológicas teñidas con hematoxilina y eosina (H&E), un paso de preprocesamiento para mejorar los métodos tradicionales de segmentación de núcleos. Cualquier estructura no nuclear es mapeada a un espacio de Noiselet a diferentes niveles de resolución, donde un clasificador es entrenado para reconocer los coeficientes de Noiselet de esta proyección. El enfoque propuesto se evaluó con dos conjuntos de datos de múltiples órganos anotados manualmente, comparando la segmentación de los núcleos obtenida por un algoritmo de Watershed más el enfoque presentado con el método de Watershed solamente. (Texto tomado de la fuente)
dc.description.abstractThis study presents a novel strategy to characterize and remove non-nuclei signal (noise) in histopathological images stained with hematoxylin and eosin (H&E), a preprocessing step to improve traditional nuclei segmentation methods. Any non nuclei structure is mapped to a Noiselet space at different resolution levels, where a classic classifier is trained to recognize the Noiselet coefficients of this projection. The proposed approach was evaluated with two multi-organ datasets manually annotated, comparing the nuclei segmentation obtained by a Watershed algorithm plus the presented approach against the watershed method alone.
dc.format.extentxi. 37 páginas
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherUniversidad Nacional de Colombia
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject.ddc620 - Ingeniería y operaciones afines::628 - Ingeniería sanitaria
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::004 - Procesamiento de datos Ciencia de los computadores
dc.subject.meshPatología
dc.subject.meshPathology
dc.titleNon-Nuclei Tissue Characterization of Histopathological Images: A Processing Step to Improve Nuclei Segmentation Methods
dc.typeTrabajo de grado - Maestría
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.publisher.programBogotá - Medicina - Maestría en Ingeniería Biomédica
dc.contributor.educationalvalidatorMoncayo Martinez Ricardo Alexander
dc.contributor.researchgroupCim@Lab
dc.description.degreelevelMaestría
dc.description.researchareaDigital Pathology
dc.identifier.instnameUniversidad Nacional de Colombia
dc.identifier.repoRepositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourlhttps://repositorio.unal.edu.co/
dc.publisher.facultyFacultad de Medicina
dc.publisher.placeBogotá, Colombia
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotá
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.subject.lembCélulas - patología
dc.subject.lembCells - pathology
dc.subject.proposalEnfermedad del cáncer
dc.subject.proposalhistopatología
dc.subject.proposaleliminación de señal de ruido
dc.subject.proposaltransformación Noiselet
dc.subject.proposalseñal de núcleos
dc.subject.proposalcancer disease
dc.subject.proposalhistopathology
dc.subject.proposalnoise signal removal
dc.subject.proposalNoiselet transformation
dc.subject.proposalnuclei signal
dc.title.translatedCaracterización de tejidos no nucleares de imágenes histopatológicas: un paso de procesamiento para mejorar los métodos de segmentación de núcleos
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dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
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dc.type.redcolhttp://purl.org/redcol/resource_type/TM
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2
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