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The scale of magnification/pixel density was calibrated, and each mitochondrion per image was counted and its area quantified (ImageJ).
The total area of skeletonized dendrites in each image, corresponding to the total dendrite length, was counted by the particle analysis command, and the total number of neuron in each image was counted based on nuclear staining with DAPI.
The number of positive cells in each image was counted manually.
The total number of whole cells seen in each image was counted.
For this evaluation, a real image was counted as a positive and a synthetic image as a negative.
After the hotspots were identified, total number of vessels per selected image was counted at × 400 magnification.
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Since the orientation and shift parameters of each module are searched within a local range and only the local area of the particle image is counted, we call this method as the local optimization refinement algorithm (LO-refinement).
For a stand-mounted air conditioner, the number of circles in the image is counted after extracting the edge (for wind hole) as shown in Fig. 4 and used as additional information along with the learning/recognition results.
The cells per image were counted and analysed compared to control transfected cells.
For semiquantification of MitoSOX fluorescence, five non adjacent images were taken for each group under identical exposure condition and cell numbers (Hoecst positive nuclei) in each image were counted.
Five pictures of each well were taken and the cells in each image were counted.
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