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Given a binary mask of the K-means segmentation, we assign the superpixels having 80% positive pixels as foreground candidates and their dilated superpixels as background candidates.
First, a global threshold value is determined by Otsu's method [6] and image thresholding is performed to extract the binary mask of the foreground, i.e., the particle region on an image.
Nuclear regions were selected manually and multiplied with a binary mask of the respective ROIs to obtain the mean centromeric fluorescence intensity.
A binary mask of the cell with the inside set to 1 was obtained by a separate customized Matlab program using the gray scale images with black background that was previously generated.
For each frame, the phase image is converted to a binary mask of the cell colony.
From the binary mask of the LD population, each LD of radius rLD was given a new radius rLD + rA.
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CaV1.2 cluster area sizes were determined using binary masks of the images in ImageJ/Fiji.
To this end, binary masks of the prescribed voxel volumes were first generated in the space of the FSE images.
Mean fluorescence intensities of EGFR-mCitrine and pY845 at the RE were obtained by using binary masks of the RE, generated from thresholded BFP-Rab11a images.
Binary masks of the RE were generated from thresholded BFP-Rab11a images and for endosomal EGFR from thresholded EGFR-mCitrine images.
Volume was measured in 3D reconstructions using custom-made image-processing routines written in SCIAN-Soft, which involved thresholding, manual and automated segmentation, and generation of binary masks of the habenular neuropil and IPN.
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