Arabidopsis Thaliana Automatic Cell File Detection and Cell Length Estimation

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2011

Autores

Pedro Quelhas (Autor) Outra; Jeroen Nieuwland (Autor) Outra; Walter Dewitte (Autor) Outra; Ana Maria Mendonca (Autor) FEUP; Jim Murray (Autor) Outra; Aurelio Campilho (Autor) FEUP

Ata de Conferência Internacional

Título: Image Analysis and Recognition

Páginas: 1-11

8th International Conference, ICIAR 2011

Burnaby, BC, Canada, June 22-24, 2011

Indexação

ISI Web of Knowledge - 5 Citações

Scopus - 5 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

Outras Informações

ID Authenticus: P-002-WYP

DOI: 10.1007/978-3-642-21596-4_1

Abstract (EN): In plant development biology, the study of the structure of the plant's root is fundamental for the understanding of the regulation and interrelationships of cell division and cellular differentiation. This is based on the high connection between cell length and progression of cell differentiation and the nuclear state. However, the need to analyse a large amount of images from many replicate roots to obtain reliable measurements motivates the development of automatic tools for root structure analysis. We present a novel automatic approach to detect cell files, the main structure in plant roots, and extract the length of the cells in those files. This approach is based on the detection of local cell file characteristic symmetry using a wavelet based image symmetry measure. The resulting detection enables the automatic extraction of important data on the plant development stage and of characteristics for individual cells. Furthermore, the approach presented reduces in more than 90% the time required for the analysis of each root, improving the work of the biologist and allowing the increase of the amount of data to be analysed for each experimental condition. While our approach is fully automatic a user verification and editing stage is provided so that any existing errors may be corrected. Given five test images it was observed that user did not correct more than 20% of all automatically detected structure, while taking no more than 10% of manual analysis time to do so.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11