Segmentation is one of the most important steps in microscopy image analysis. Unfortunately, most of the methods use fluorescence images for this task, which is not suitable for analysis that requires a knowledge of area occupied by cells and an experimental design that does not allow necessary labeling. In this protocol, we present a simple method, based on edge detection and morphological operations, that separates total area occupied by cells from the background using only brightfield channel image. The resulting segmented picture can be further used as a mask for fluorescence quantification and other analyses. The whole procedure is carried out in open source software Fiji
The increasing amounts of microscopy data generated in cell biology requires the development of auto...
Cell nucleus segmentation remains an open and challenging problem especially to segment nuclei in ce...
The application of fluorescence microscopy in cell biology often generates a huge amount of imaging ...
The detection and segmentation of adherent eukaryotic cells from brightfield microscopy images repre...
Fluorescence microscopy is the standard tool for detection and analysis of cellular phenomena. This ...
Fluorescence microscopy is the standard tool for detection and analysis of cellular phenomena. This ...
Segmentation of transparent cells in brightfield microscopy images could facilitate the quantitative...
Abstract. The automatic subcellular localisation of proteins in living cells is a critical step in d...
Tscherepanow M, Zöllner F, Kummert F. Automatic Segmentation of Unstained Living Cells in Bright-Fie...
Tscherepanow M, Zöllner F, Kummert F. Classification of Segmented Regions in Brightfield Microscope ...
Automatic cell segmentation has various applications in cytometry, and while the nucleus is often ve...
New technological advances in automated microscopy have given rise to large volumes of data, which h...
Segmenting transparent phase objects, such as biological cells from brightfield microscope images, i...
Abstract. Automatic cell segmentation has various applications in cytometry, and while the nucleus i...
In this thesis, we present a new method for the automatic segmentation of mammalian cancer cells fro...
The increasing amounts of microscopy data generated in cell biology requires the development of auto...
Cell nucleus segmentation remains an open and challenging problem especially to segment nuclei in ce...
The application of fluorescence microscopy in cell biology often generates a huge amount of imaging ...
The detection and segmentation of adherent eukaryotic cells from brightfield microscopy images repre...
Fluorescence microscopy is the standard tool for detection and analysis of cellular phenomena. This ...
Fluorescence microscopy is the standard tool for detection and analysis of cellular phenomena. This ...
Segmentation of transparent cells in brightfield microscopy images could facilitate the quantitative...
Abstract. The automatic subcellular localisation of proteins in living cells is a critical step in d...
Tscherepanow M, Zöllner F, Kummert F. Automatic Segmentation of Unstained Living Cells in Bright-Fie...
Tscherepanow M, Zöllner F, Kummert F. Classification of Segmented Regions in Brightfield Microscope ...
Automatic cell segmentation has various applications in cytometry, and while the nucleus is often ve...
New technological advances in automated microscopy have given rise to large volumes of data, which h...
Segmenting transparent phase objects, such as biological cells from brightfield microscope images, i...
Abstract. Automatic cell segmentation has various applications in cytometry, and while the nucleus i...
In this thesis, we present a new method for the automatic segmentation of mammalian cancer cells fro...
The increasing amounts of microscopy data generated in cell biology requires the development of auto...
Cell nucleus segmentation remains an open and challenging problem especially to segment nuclei in ce...
The application of fluorescence microscopy in cell biology often generates a huge amount of imaging ...