1. 3D median spatial filter: This is a non-linear filtering technique that removes noise from the image while preserving the edges. This pre-processing step improves results of later image processing (e.g., edge detection). During 3D median filtering, an X-Y-Z matrix calculates a median value in X, Y, and Z pixels in each dimension and replaces those pixels with the median value. For processing our neutron and X-ray datasets, we used X = 5, Y = 5, and Z = 7 values in ImageJ. 2. Unsharp mask filter: This is an image sharpening filter. An image is sharpened by subtracting a blurred version of the image from itself. The blurred image is created using a Gaussian blur function. The Gaussian blur or smoothing is an image-blurring low-pass filter that uses a Gaussian function to attenuate the high frequency signals. Next, the unsharp mask is combined with the original positive image, thus creating an image that is less blurry than the original (Eq. S1-2).