Trabalho Apresentado em Evento

Automatic identification of mycobacterium tuberculosis with conventional light microscopy

This article presents an automatic identification method of mycobacterium tuberculosis with conventional microscopy images based on Red and Green color channels using global adaptive threshold segmentation. Differing from fluorescence microscopy, in the conventional microscopy the bacilli are not ea...

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Autor principal: Costa, Marly Guimarães Fernandes
Outros Autores: Costa Filho, Cícero Ferreira Fernandes, Sena, Juliana F., Salem, Júlia Ignez, Lima, Mari O. de
Grau: Trabalho Apresentado em Evento
Idioma: English
Publicado em: Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology" 2020
Assuntos:
Automation
Electronic Data Interchange
Microscopy, Fluorescence
Adaptive Threshold Segmentations
Automatic Identifications
Green Colors
Light Microscopies
Microscopy Images
Mycobacterium Tuberculosis
Segmentation Methods
Segmented Images
Color
Algorithm
Artificial Intelligence
Pattern Recognition, Automated
Computer Assisted Diagnosis
Cytology
Evaluation Study
Image Enhancement
Methodology
Microscopy
Mycobacterium Tuberculosis
Reproducibility
Sensitivity And Specificity
Algorithms
Artificial Intelligence
Image Enhancement
Image Interpretation, Computer-assisted
Microscopy
Mycobacterium Tuberculosis
Pattern Recognition, Automated
Reproducibility Of Results
Sensitivity And Specificity
Acesso em linha: https://repositorio.inpa.gov.br/handle/1/19999

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