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| Titel: |
Algorithms for cytoplasm segmentation of fluorescence labelled cells |
| Auteur: |
Carolina Wählby Joakim Lindblad Mikael Vondrus Ewert Bengtsson Lennart Björkesten |
| Verschenen in: |
Analytical cellular pathology |
| Paginering: | Jaargang 24 (2003) nr. 2-3 pagina's 101-111 |
| Jaar: |
2003-01-03 |
| Inhoud: |
Automatic cell segmentation has various applications in cytometry, and while the nucleus is often very distinct and easy to identify, the cytoplasm provides a lot more challenge. A new combination of image analysis algorithms for segmentation of cells imaged by fluorescence microscopy is presented. The algorithm consists of an image pre-processing step, a general segmentation and merging step followed by a segmentation quality measurement. The quality measurement consists of a statistical analysis of a number of shape descriptive features. Objects that have features that differ to that of correctly segmented single cells can be further processed by a splitting step. By statistical analysis we therefore get a feedback system for separation of clustered cells. After the segmentation is completed, the quality of the final segmentation is evaluated. By training the algorithm on a representative set of training images, the algorithm is made fully automatic for subsequent images created under similar conditions. Automatic cytoplasm segmentation was tested on CHO-cells stained with calcein. The fully automatic method showed between 89% and 97% correct segmentation as compared to manual segmentation. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
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