Machine Learning: Advanced Image Segmentation Using ilastik.
Methods Mol Biol
; 2040: 449-463, 2019.
Article
en En
| MEDLINE
| ID: mdl-31432492
Segmentation is one of the most ubiquitous problems in biological image analysis. Here we present a machine learning-based solution to it as implemented in the open source ilastik toolkit. We give a broad description of the underlying theory and demonstrate two workflows: Pixel Classification and Autocontext. We illustrate their use on a challenging problem in electron microscopy image segmentation. After following this walk-through, we expect the readers to be able to apply the necessary steps to their own data and segment their images by either workflow.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Procesamiento de Imagen Asistido por Computador
/
Programas Informáticos
/
Aprendizaje Automático
Límite:
Animals
Idioma:
En
Revista:
Methods Mol Biol
Asunto de la revista:
BIOLOGIA MOLECULAR
Año:
2019
Tipo del documento:
Article
País de afiliación:
Alemania