![]() ![]() content of this page has not been vetted since shifting away from MediaWiki. A Novel ImageJ Macro for Automated Cell Death Quantitation in the Retina. Maidana DE, Tsoka P, Tian B, Dib B, Matsumoto H, Kataoka K, Lin H, Miller JW, Vavvas DG.In case you have any comments, suggestions, or any difficulties with your images, just send us a message! References Apply the same settings to the entire dataset if comparison is intended. Next, adjust saturation until cells are easily identifiable. First, reduce background as much as possible to remove any fragments. A: Check your acquisition and post-processing parameters for the channel of interest.Q: I cannot get accurate segmentation or counting.A: Please cite or reference this work as follows: Maidana DE, Tsoka P, Tian B, Dib B, Matsumoto H, Kataoka K, Lin H, Miller JW, Vavvas DG.Please acknowledge previous work that helped or inspired you, and share your contribution with the scientific community! A: Yes, you can modify the code to develop new macros or plugins.To have an idea of suitable images for this macro, we recommend to review the image dataset used for validation: Significant Shadowing: Shadowing will render incomplete layer segmentation.Uncentered Image: For best results, acquire images centered in frame.Indistinguishable Retinal Layers: The macro cannot distinguish between the ONL and INL if you can’t either!.Image Focus: Uneven image focus will render incomplete layer segmentation.Staining quality: Images need to have an intense cell staining and low background noise.We considered this magnification the most suitable to assess a reasonably large area without missing out cell morphology details. Acquisition: The macro was designed for images acquired with a 20x/0.8 air objective.Results are saved as an Excel (.xls) file. **Threshold Sensitivity**: Select the threshold protocol for cell counting.Ī processed image is generated and saved in a new directory. Channels: Choose the cells of interest in either the green, red, or combined channels.Threshold Sensitivity: Choose between a standard and high sensitivity threshold, in case you need to detect cells with low intensity values.Retina Area Selection: Choose between automated ONL & INL segmentation or manual freehand selection.If “Mostly not rounded” is selected, mostly not circular cells will be counted (Circularity 0.0-0.5). If “Mostly rounded” is selected, mostly circular cells will be counted (Circularity 0.5-1.0). Cell Roundness: If “All” is selected, all thresholded cells will be counted (Circularity 0-1).Minimum and Maximum Cell Area: Input the previously measured and selected cutoff values.The rescaled image will be saved as a copy. Image Rescaling Options: If the image is larger that 1300 pixels width, it will be rescaled to speed up the processing.Native Spatial Scale: Input the current image scale in pixels/microns.Image Native Resolution: Displays the imported image resolution.Microscope Magnification: Displays the working 20x objective magnification.Settings Dialog: Input the spatial scale obtained from the image metadata or microscope.Īfter importing a TIFF image and executing the counter, the following settings should be selected: These measurements can be performed in Fiji with the freehand selection tool, after setting the spatial scale factor. Minimum Cell Size & Maximum Cell Area (µm 2): These values should be determined upfront, according to your image dataset.Microscope Spatial Scale: Pixels/microns.Digital Image: Files should be in TIFF format.TUNEL Cell Counter: Macro should be installed in Fiji (ImageJ).The following are required to execute this tool: TUNEL Cell Counter: Input a fluorescent-labeled retinal image for ONL & INL layer segmentation and cell quantitation. It segments retinal outer nuclear (ONL) and inner nuclear layers (INL) and quantitates fluorescent-labelled cells in these layers. TUNEL Cell Counter is a customizable tool that processes digital images from retinal cryosections. The current components of these toolkit are: TUNEL Cell Counter and RETINA Cell Heatmap. The purpose of the RETINA Analysis Toolkit is to perform fast quantitation of digital RGB images from retina cryosections, acquired by fluorescent microscopes. RETINA Analysis Toolkit is a free macro toolkit designed and developed for Fiji (ImageJ). ![]()
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