4/30/2023 0 Comments Cellprofiler minimizing contrastThis is accomplished by using a single template image, “PlateTemplate.png”, to represent the image region corresponding to the interior of the plastic plate. This pipeline is flexible regarding the placement of each plate within the image, in that specific modules allow for CellProfiler to find the plate anywhere within the image, even if the position of the plate within the image varies from sample to sample. Example images and corresponding CellProfiler pipeline (see step 4)Īdjust the plate template image for your particular test images (if needed). This protocol was written for CellProfiler version 2.1.0. CellProfiler is optimized to take advantage of multiple computing processors on a single computer, but large image sets (greater than ~500 images) will likely require a computing cluster (see Alternate Protocol).ĭecompression software (e.g., WinZip, Stuffit) for unpacking compressed files, if not already included in your operating system.ĬellProfiler software (see step 1). The example image pipeline demonstrated here will be processed in ~1 minute per image on a single computer with a 2.67 GHz processor and 8 GB RAM. A complete list of compatible operating systems can be found at. CellProfiler is available for Macintosh, Windows, and Unix/Linux. A 64-bit operating system is strongly recommended. See Critical Parameters for more information about acquiring images and image file types.Ĭomputer with at least 4 GB of RAM and multiple processors each running at least 2 GHz. More than 100 file formats are currently readable by CellProfiler, including BMP, GIF, JPG, PNG, TIF, DIB, LSM, and FLEX. While this example only analyzes one image, it is possible to analyze hundreds of images on a single computer, or hundreds of thousands of images using a computing cluster (see Alternate Protocol). The images can be located within subfolders and need not be in a particular order or follow a particular naming convention. 2007) see Critical Parameters for guidance. Images can be taken with a flatbed scanner or digital camera ( Dahle et al. CellProfiler has been cited in more than a thousand papers and validated for a wide variety of biological applications, including yeast colony counting and classification, cell microarray annotation, yeast patch assays, cell-cycle classification, mouse tumor quantification, wound healing assays, and tissue topology measurement, as well as analysis of fluorescence microscopy images for measurement of cell size and morphology, cell cycle distributions, fluorescence staining levels, and other features of individual cells in images ( Lamprecht, Sabatini, and Carpenter 2007 Carpenter et al. The protocol uses the open-source, freely downloadable software package, CellProfiler. This unit outlines a protocol for the automated counting and analysis of yeast colonies growing on agar plates however, the methods described can be adapted to a wide variety of biological “objects” and can be used to measure a wide variety of features for each object. It is less tedious, more objective and quantitative, and, while the set up can be time-consuming, the analysis itself is usually much faster for large sample sets. Acquiring images and analyzing them automatically with image analysis software has several advantages over simple visual inspection. Many experiments in a biology laboratory involve visual inspection, such as examining yeast colonies or growth patches on agar plates, or examining live or stained cell samples by microscopy.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |