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Using ImageJ, the extent of dye loading was measured by drawing a region of interest (ROI) around individual cells and calculating the mean pixel intensity for the ROI.
The counts in the anterior and posterior images in a ROI around the kidney were recorded and the counts in a background ROI located caudal to the kidney ROI were subtracted.
Firstly, based on these points, we can select a region of interest (ROI) around the hand.
According to co-founder Edward Saatchi, the goal is to show a real ROI around deploying its system.
The number of counts in a region-of-interest (ROI) around the source in the images was determined and plotted versus the depth.
First, the optical disk is found and a circular region of interest (ROI) around it is selected in the segmented image.
Then the candidate edges are achieved by defining a small region of interest (ROI) around the predicted horizon location, and the final horizon is acquired according to the statistic appearance of the local region.
To evaluate our method, a surrogate was designed for each handle such that when modeled as a phalanx it would generate a ROI around the cells under its supports; the classification F-score was above 0.95 for both handles.
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To discriminate fluorescence loss in different cellular regions, background fluorescence was subtracted from images and ROIs drawn around the outside perimeter, inside perimeter, nucleus, and Golgi of cells.
The latter was done by manually drawing ROIs around each joint (Hermes, Nuclear Diagnostics, Sweden).
We measured the optical spectra from HS images by defining ROIs around either individual cells ('cell Ror') or around each NPC within the cells ('NPC ROI'NPC
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