The area or volume of the image occupied by signal is returned as the mitochondrial footprint, the units of which will depend on how the image has been calibrated. This binarized copy is overlaid upon the original image after processing as an accuracy/artifact check measure. In the binarized image, magenta represents the signal positive pixels, while the background pixels are black. Figure 2 illustrates an image after thresholding. Once the image has been binarized, the area or volume can be estimated by simply counting the number of signal positive pixels/voxels and multiplying by the area or volume of the pixel/voxel approximated as a rectangle or rectangular prism. If you find an issue arises using a specific thresholding method, please open an issue using the GitHub issue tracker (only a subset were tested). So far, only global thresholds are provided, though local thresholds will be incorporated eventually. There are many thresholding methods available through ImageJ Ops. This is generated by automatic thresholding, a good overview of which available on the Auto Threshold page. One is a binary representation, which simply represents pixels as containing signal or being background. For demonstration purposes, we will be using the micrograph crop in Figure 1. MiNA extracts morphological information from two simplifications of the image. Close the site manager dialog ( Close).ĭeterming the Area/Volume of Mitochondria.Add the “StuartLab” and “Biomedgroup” sites by checking the checkbox beside the site.Navigate to the update site manager ( Manage update sites).To add the update site in your installation of Fiji: By this method, you will receive automatic updates everytime the updater is run ensuring you get new features and bug fixes as soon as they are available. To install MiNA and the additional plugins, scripts, and macro tools our lab uses bundled with it, we suggest adding our update site ( “StuartLab”). The values are reported in a table and overlays (or a 3D rendering) are generated to assess the accuracy of the analysis. In short, the tool estimates mitochondrial footprint (or volume) from a binarized copy of the image as well as the lengths of mitochondrial structures using a topological skeleton. The workflow makes use of ImageJ Ops, 3D Viewer, Skeletonize (2D/3D), Analyze Skeleton 1, and Ridge Detection 2 3. MiNA is a simplified workflow for analyzing mitochondrial morphology using fluorescence images or 3D stacks in Fiji. If you’d like to help, check out the how to help guide! The content of this page has not been vetted since shifting away from MediaWiki.
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