A hybrid approach for Arabidopsis root cell image segmentation

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

Autores

Marcuzzo, M (Autor) Outra; Quelhas, P (Autor) Outra; Campilho, A (Autor) Outra; Mendonca, AM (Autor) FEUP; Campilho, A (Autor) FEUP

Ata de Conferência Internacional

Título: Image Analysis and Recognition

Páginas: 739-749

5th International Conference on Image Analysis and Recognition (ICIAR 2008)

Póvoa de Varzim, Portugal, June 25-27, 2008

Indexação

ISI Proceedings

ISI Web of Knowledge - 5 Citações

Scopus - 7 Citações

Outras Informações

ID Authenticus: P-008-NG7

DOI: 10.1007/978-3-540-69812-8_73

Abstract (EN): In vivo observation and tracking of the Arabidopsis thaliana root meristem, by time-lapse confocal microscopy, is important to understand mechanisms like cell division and elongation. The research herein described is based on a large amount of image data, which must be analyzed to determine the location and state of cells. The automation of the process of cell detection/marking is an important step to provide research tools for the biologists in order to ease the search for special events, such as cell division. This paper discusses a hybrid approach for automatic cell segmentation, which selects the best cell candidates from a starting watershed-based image segmentation and improves the result by merging adjacent regions. 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 merging criterion is based on edge strength along the line that connects adjacent cells' centroids. The resulting segmentation is largely pruned of badly segmented and over-segmented cells, thus facilitating the study of cell division.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11