Long-term tracking of budding yeast cells in brightfield microscopy: CellStar and the Evaluation Platform.
J R Soc Interface
; 14(127)2017 02.
Article
en En
| MEDLINE
| ID: mdl-28179544
With the continuous expansion of single cell biology, the observation of the behaviour of individual cells over extended durations and with high accuracy has become a problem of central importance. Surprisingly, even for yeast cells that have relatively regular shapes, no solution has been proposed that reaches the high quality required for long-term experiments for segmentation and tracking (S&T) based on brightfield images. Here, we present CellStar, a tool chain designed to achieve good performance in long-term experiments. The key features are the use of a new variant of parametrized active rays for segmentation, a neighbourhood-preserving criterion for tracking, and the use of an iterative approach that incrementally improves S&T quality. A graphical user interface enables manual corrections of S&T errors and their use for the automated correction of other, related errors and for parameter learning. We created a benchmark dataset with manually analysed images and compared CellStar with six other tools, showing its high performance, notably in long-term tracking. As a community effort, we set up a website, the Yeast Image Toolkit, with the benchmark and the Evaluation Platform to gather this and additional information provided by others.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Schizosaccharomyces
/
Procesamiento de Imagen Asistido por Computador
/
Rastreo Celular
Idioma:
En
Revista:
J R Soc Interface
Año:
2017
Tipo del documento:
Article
País de afiliación:
Francia
Pais de publicación:
Reino Unido