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Lut imagej4/5/2023 Select the LUT, which you want to apply, with Image/Lookup Tables -> Fire (just as an example). The Fill With choice does not matter, but choose Ramp. If you are not working with a 32bit image, make a dummy image with File/New/Image…. This hint follows advice from Bob Dougherty: 032, Pixel Aspect Ratio = 1, Unit of Length = mmĪdd the scale bar with Analyze/Tools/Scale Bar and make it for example 2mm long, font 12 pt, not bold, position lower left (or whatever you like). Let us assume that one voxel has the dimensions 32 µm x 32 µm x 32 µm.Īnalyze/Set Scale and give Distance in pixels = 1, Known Distance =. If you do not check this option you can add it later with the following commands. These images can be scaled already to metric units during their import with KHKs_Scanco_ISQ_FileReader. We use microcomputed tomography images usually. You can scale ImageJ pixels to metric units. Now all 8bit stacks for the VolumeJ thickness rendering will have the same scale. Afterwards you convert all images to 8bit. Then you can check: “Propagate through all Images” and apply this adjustment to all relevant images. Then you use for the 32-bit-images: Image > Adjust > Brightness > Set: Min = your minimum value, Max = your desired maximum value. You should determine the minimum and maximum values which you want to color code in your project.įor ease of explanation I suggest to open all distance transformation images and determine their maximum. How to set the same color scale for several samples The following description shows one way to get the same color scale for all samples of your project. If you just convert the 32-bit-stacks to 8-bit-stacks, then every image of your project probably has a different scale for the LUTcode. The VolumeJ plugin requires a 8-bit-stack color map. The local thickness stacks are 32-bit-stacks. For the color code, which will be rendered to the surface, we use the local thickness output of Bob Dougherts’s 3D Distance Transformation implementation. The volumes are 8-bit-stacks from any kind of segmentation. The following section provides some tipps and tricks for the usage of ImageJ.
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