The tracing algorithm subsequently computes and shows the "optimal" path from the current mouse position in the image to the clicked point. The actual tracing of neurites is initiated by moving the mouse to the beginning of a neurite of interest and clicking the (left) mouse button. This preprocessing may take a few seconds (depending on the size of the image and the computing power). The first time this button is pressed, the program performs some image processing operations required for the tracing algorithm. This facilitates tracing multiple images.Īdd tracings. If so, the next (or previous) image in the folder can be loaded by pressing the right arrow (or left arrow) key on the keyboard (if the current image is active). The first time an image is loaded using the NeuronJ toolbar, the program also checks if there are other images in the same folder (only files with extension ".tif", ".tiff", ".gif", or ".jpg" are considered). It is also possible to load a data file manually, replacing the current tracings and settings. Parameter settings, type and cluster names, and type colors contained in the file are also loaded and replace the current settings. If so, it will load it automatically and display the tracings. If you load an image, NeuronJ checks if there exists a data file for that image (must be a file in the same folder and with the same base name as the image file, but with extension ".ndf"). Every time a new image is loaded, NeuronJ automatically closes the previous image.įiles containing tracings and settings saved by NeuronJ have the extension ".ndf", which stands for "NeuronJ data file". Upon pressing Open, the selected image is loaded and NeuronJ "attaches" itself to the image. NeuronJ can handle only images that have been loaded using this dialog, not images loaded with ImageJ or images already open when NeuronJ was started. Opens a dialog for selecting and loading either an image (only 8-bit gray-scale and indexed color images are accepted) or previously saved tracings (including corresponding settings). We repeat these steps for every nucleus and golgi, then you have your overall relationship.Load image/tracings. So, we finish this up with finding the angle of A (adjacent to hypotenuse angle): Step 10: And now we can use these to find the hypotenuse( ) Step 9: Calculate the length of A to C (adjacent) and C to B (Opposite) In some cases we may need to invert numbers in order for this to work, but this can be handled in scripting within excel or fiji if needed. – Golgi and nuclear XY points become A XY and B XY Step 8: identify the three point positions of a right-side triangle. SO: we have these two numbers, how can we figure out orientation?īasically we can create a right sided triangle, wherein the points of the triangle form the origins and intersection of the two objects (nucleus and golgi) and the third point is the intersection of the two points at 90 degrees. In the case that this is not true we could employ skeletonizing from the nuclear signal, but that’s for another time. Based on the XY coordinates, we can assume in this image that the nearest golgi XY location to a dapi XY location is from the same cell. Sort the results via the Centroid X/Y values. Golgi Thresholded – In this example I had too many objects Step 5: perform “particle Analysis” on both images. Step 4: Threshold the other two channels. Step3: close the red channel (mitochondrial signal). Step 2: Separate the channels into R,G and B channels using the Image -> Color -> Split Channels command. I’ve posted this here as I think it’s a nice example of employing trig for imaging. The cell in this case was in one channel, and the golgi was in another. The object was a nucleus, and the orientation was indicated by the position inside of the nucleus of the Golgi. I had a question posed by a coworker who wanted to identify the rotational orientation of an object.
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