Biological image analysis software packages offer tools to analyze microscope images of cells. Some of these tools allow quantitative analysis through interactive processing. High-throughput applications employing microscopy for cell-based assays require analysis of large number of images. We describe here acquisition and analysis of cell images in high throughput automated mode aiming to screen for effects in structure and molecular organization of cellular components recorded by high resolution cell images and in cell motility.
[Show abstract][Hide abstract] ABSTRACT: Automated segmentation of fluorescently-labeled cell nuclei in 3D confocal microscope images is essential to many studies involving morphological and functional analysis. A common source of segmentation error is tight clustering of nuclei. There is a compelling need to minimize these errors for constructing highly automated scoring systems.
A combination of two approaches is presented. First, an improved distance transform combining intensity gradients and geometric distance is used for the watershed step. Second, an explicit mathematical model for the anatomic characteristics of cell nuclei such as size and shape measures is incorporated. This model is constructed automatically from the data. Deliberate initial over-segmentation of the image data is performed, followed by statistical model-based merging. A confidence score is computed for each detected nucleus, measuring how well the nucleus fits the model. This is used in combination with the intensity gradient to control the merge decisions.
Experimental validation on a set of rodent brain cell images showed 97% concordance with the human observer and significant improvement over prior methods.
Combining a gradient-weighted distance transform with a richer morphometric model significantly improves the accuracy of automated segmentation and FISH analysis.
Cytometry Part A 11/2003; 56(1):23-36. DOI:10.1002/cyto.a.10079 · 2.93 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The cytoskeleton consists of complex arrays of fibers that play indispensable roles in cell structure and function. The cytoskeletal fibers are concertedly involved in numerous cellular processes, including cell adhesion, locomotion, intracellular transport, and cell division. The organization of the cytoskeleton was extensively studied, mainly by immunofluorescence microscopy, yet these studies were mostly qualitative, and a reliable quantitative approach for determining fiber structure and distribution is still missing.
In this study we developed algorithms for filament feature extraction, based on fluorescence microscopy. These algorithms are robust against blurring by slight defocus, high background, and noise, and are applicable to both fixed, immunolabeled cells and live cells expressing fluorescently tagged cytoskeletal proteins. The implemented FiberScore program is used in order to recognize, segment, and quantify various structural parameters of the cytoskeleton, including total fiber-associated fluorescence, as well as fiber length and orientation. Furthermore, these parameters can be determined for different cytoskeletal proteins in the same sample tagged with multiple-fluorescent labels, and the results can be correlated with other cellular parameters.
FiberScore was used here for the quantification of simultaneous changes in microtubule and actin filaments induced by the microtubule-disrupting drug nocodazole. Actin filaments, which are reported to respond reciprocally to microtubule disruption, are found to be affected by both immediate and delayed signals.
Analysis of the organization of fibers by the FiberScore algorithm allows quantification of the cytoskeletal signature of cells and offers reliable multiparametric functional assays for effects of drugs and other perturbations evaluated on a cell-by-cell basis.
Cytometry Part A 07/2003; 54(1):8-18. DOI:10.1002/cyto.a.10053 · 2.93 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This paper describes a technique of visualizing tracks of cultured cells moving on a glass substrate covered with gold particles. It leads to the following observations: -If the tracks of many cells are examined, cell line characteristic track patterns become apparent. -In several cases, second or third generation descendents of 3T3 cells were observed to repeat track patterns of their ancestor cell. -If a 3T3 cell collides with another 3T3 cell or a nonmigrating BSC-1 cell, it forms an outgoing track from the impact area as if the cell was elastically reflected at the target.
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.