Repositorio Institucional
Repositorio Institucional
CONICET Digital
  • Inicio
  • EXPLORAR
    • AUTORES
    • DISCIPLINAS
    • COMUNIDADES
  • Estadísticas
  • Novedades
    • Noticias
    • Boletines
  • Ayuda
    • General
    • Datos de investigación
  • Acerca de
    • CONICET Digital
    • Equipo
    • Red Federal
  • Contacto
JavaScript is disabled for your browser. Some features of this site may not work without it.
  • INFORMACIÓN GENERAL
  • RESUMEN
  • ESTADISTICAS
 
Artículo

Morphological characterization of colorectal pits using autofluorescence microscopy images

Erbes, Luciana AriadnaIcon ; Zeitoune, Angel AlbertoIcon ; Torres, Humberto MaximilianoIcon ; Casco, Victor Hugo; Adur, Javier FernandoIcon
Fecha de publicación: 07/2019
Editorial: Instituto Brasileiro de Estudos e Pesquisas de Gastroenterologia e Outras Especialidades
Revista: Arquivos de Gastroenterologia
ISSN: 0004-2803
e-ISSN: 1678-4219
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Ciencias de la Información y Bioinformática

Resumen

Background: Colorectal cancer (CRC) is one of the most prevalent pathologies. Its prognosis is linked to the early detection and treatment. Currently diagnosis is performed by histological analysis from polyp biopsies, followed by morphological classification. Kudo?s pit pattern classification is frequently used for the differentiation of neoplastic colorectal lesions using hematoxylin-eosin (H&E) stained samples. Few articles have reported this classification with image software processing, using exogenous markers over the samples. The processing of autofluorescence images is an alternative that could allow the characterization of the pits from the crypts of Lieberkühn, bypassing staining techniques. Objective: Processing and analysis of widefield autofluorescence microscopy images obtained by fresh colon tissue samples from a murine model of CRC in order to quantify and characterize the pits morphology by measuring morphology parameters and shape descriptors. Methods: Two-dimensional (2D) segmentation, quantification and morphological characterization of pits by image processing applied using macro programming from FIJI. Results: Type I is the pit morphology prevailing between 53 and 81% in control group weeks. III-L and III-S types were detected in reduced percentages. Between the 33 and 56% of type I was stated as the prevailing morphology for the 4th, 8th and 20th weeks of treated groups, followed by III-L type. For the 16th week, the 39% of the pits was characterized as III-L type, followed by type I. Further, pattern types as IV, III-S and II were also found mainly in that order for almost all of the treated weeks. Conclusion: These preliminaries outcomes could be considered an advance in two-dimensional pit characterization as the whole image processing, comparing to the conventional procedure, takes a few seconds to quantify and characterize non-pathological colon pits as well as to estimate early pathological stages of CRC.
Palabras clave: colorectal , cancer , classification , pattern , autofluorescence , morphology
Ver el registro completo
 
Archivos asociados
Thumbnail
 
Tamaño: 890.3Kb
Formato: PDF
.
Descargar
Licencia
info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/106790
DOI: http://dx.doi.org/10.1590/s0004-2803.201900000-37
Colecciones
Articulos (IBB)
Articulos de INSTITUTO DE INVESTIGACION Y DESARROLLO EN BIOINGENIERIA Y BIOINFORMATICA
Citación
Erbes, Luciana Ariadna; Zeitoune, Angel Alberto; Torres, Humberto Maximiliano; Casco, Victor Hugo; Adur, Javier Fernando; Morphological characterization of colorectal pits using autofluorescence microscopy images; Instituto Brasileiro de Estudos e Pesquisas de Gastroenterologia e Outras Especialidades; Arquivos de Gastroenterologia; 56; 2; 7-2019; 191-196
Compartir
Altmétricas
 
Estadísticas
Visualizaciones: 82
Descargas: 265

Enviar por e-mail
Separar cada destinatario (hasta 5) con punto y coma.
  • Facebook
  • Twitter
  • Instagram
  • YouTube
  • Sound Cloud

Los contenidos del CONICET están licenciados bajo Creative Commons Reconocimiento 2.5 Argentina License

Ministerio
https://www.conicet.gov.ar/ - CONICET

Inicio

Explorar

  • Autores
  • Disciplinas
  • Comunidades

Estadísticas

Novedades

  • Noticias
  • Boletines

Ayuda

Acerca de

  • CONICET Digital
  • Equipo
  • Red Federal

Contacto

Godoy Cruz 2290 (C1425FQB) CABA – República Argentina – Tel: +5411 4899-5400 repositorio@conicet.gov.ar
TÉRMINOS Y CONDICIONES