Automatic cell segmentation from confocal microscopy images of the Arabidopsis root

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2008

Autores

Mónica Marcuzzo (Autor) FEUP; Pedro Quelhas (Autor) FEUP; Ana Campilho (Autor) Outra; Ana Maria Mendonca (Autor) FEUP; Aurelio Campilho (Autor) FEUP

Ata de Conferência Internacional

Título: 2008 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1-4

Páginas: 712-715

5th IEEE International Symposium on Biomedical Imaging

Paris, FRANCE, MAY 14-17, 2008

Indexação

ISI Web of Knowledge - 9 Citações

Scopus - 11 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Biotecnologia ambiental

Outras Informações

ID Authenticus: P-008-NG8

DOI: 10.1109/isbi.2008.4541095

Abstract (EN): In vivo observation and tracking of cell division in the Arabidopsis thaliana root meristem, by time-lapse confocal microscopy, is central to biology research. The research herein described is based on large amount of image data, which must be analyzed to determine the location and state of cells. The possibility of automating the process of cell detection/marking is an important step to provide research tools to the biologists in order to ease the search for a special event as cell division. This paper discusses an automatic cell segmentation method, which selects the best cell candidates from a starting watershed based image segmentation. The selection of individual cells is obtained using a Support Vector Machine (SVM) classifier, based on the shape and edge strength of the cells' contour. The resulting segmentation is largely pruned of badly segmented cells, which can reduce the false positive detection of cell division. This is a good result on its own and a starting point for improvement of cell segmentation methodology.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 4