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Image acquisition and understanding in high-throughput high-resolution cell-based screening applications
- Source :
- ISBI
- Publication Year :
- 2008
- Publisher :
- IEEE, 2008.
-
Abstract
- Quantitative interpretation of microscope images is more challenging the higher the resolution of the images is. The reward is rich multi-parametric characterization of subcellular structures and detailed description of cell responses to perturbations. This information is the basis of high- throughput cell-based screening, searching to discover new drugs and understand molecular mechanisms at the cell level. We have developed a fast screening microscope acquiring high-resolution images from cells cultured in plastic-bottom multi-well plates, [1-4] and are writing an automated pipeline for the analysis of Tera Bytes of images from high throughput screens. The platform includes database for storage and retrieval of images, visualization with easy linkage of the analyzed results to the original multi-color images, segmentation of objects in images (including cells, nuclei, cytoskeletal fibers and sub-cellular organelles), multi-parametric quantification of morphological and multicolor fluorescence intensities, and statistical comparisons to control wells displayed in color coded scores on the plate graphics. This system was successfully employed for screening of the effect of drugs, gene over-expression and siRNA of diverse cellular properties, including cell adhesion, migration, survival and cytoskeletal organization.
- Subjects :
- Microscope
Drug discovery
Computer science
business.industry
Molecular biophysics
Nanotechnology
Pattern recognition
Image segmentation
Fluorescence
law.invention
Visualization
law
Organelle
Fluorescence microscope
Segmentation
Artificial intelligence
Graphics
Cell adhesion
business
Gene
Throughput (business)
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro
- Accession number :
- edsair.doi...........1635fa00acddabd8a7836cdde39ccc06