Cancer cell detection and invasion depth estimation in brightfield images

• Tipo: Artigo em Livro de Atas de Conferência Nacional
• Data: 2009

Autores

Mónica Marcuzzo (Autor) FEUP; Pedro Quelhas (Autor) FEUP; Maria Oliveira (Autor) FEUP; Ana Maria Mendonça (Autor) FEUP; Aurélio Campilho (Autor) FEUP

Ata de Conferência Nacional

Título: RecPad 2009

Páginas: 1-3

15th Portuguese Conference on Pattern Recognition

Aveiro, Portugal, 23 de Outubro de 2009

Classificação Científica

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

CORDIS: Ciências Tecnológicas > Engenharia > Engenharia biomédica

Outras Informações

Abstract (EN): The study of cancer cell invasion under the effect of different conditions is fundamental for the understanding of the cancer invasion mechanism and to test possible therapies for its regulation. To simulate invasion across tissue basement membrane, biologists established in vitro assays with cancer cells invading extracellular matrix components. However, analysis of such assays is manual, being timeconsuming and error-prone, which motivates an objective and automated analysis tool. Towards automating such analysis we present a methodology to detect cells in 3D matrix cell assays and correctly estimate their invasion, measured by the depth of the penetration in the gel. Detection is based on the sliding band filter, by evaluating the gradient convergence and not intensity. As such it can detect low contrast cells which otherwise would be lost. For cell depth estimation we present a focus estimator based on the convergence gradient¿s magnitude. The final cell detection¿s precision and recall are of 0.896 and 0.910 respectively, and the average error in the cell¿s position estimate is of 0.41µm, 0.37µm and 3.7µm in the x, y and z directions, respectively.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 3