TABLE 1.
Differences in Termini Counts among Different Micrometers per Pixel and Image Processing Iterations
| Line number | A |
B |
C |
D |
E |
F |
G |
H |
|---|---|---|---|---|---|---|---|---|
| Lines/frame at scanning | Target particle size (pixel2) | Original image (counts) | Median filter (counts) | Optimized method (counts) | Gaussian filter (sigma values) | Percent of counts relative to highest resolution | Relative data file size | |
| 1 | 8192 | ≥320 | 641 | 558 | 470 | 100 | 100% | 74× |
| 2 | 4096 | ≥80 | 935 | 584 | 522 | 100 | 111% | 18.7× |
| 3 | 2048 | ≥20 | 1456 | 578 | 508 | 50 | 108% | 4.6× |
| 4 | 950 | ≥4 | 1915 | 986 | 552 | 50 | 117% | 1× |
| 5 | 512 | ≥1 | 2307 | 485 | 765 | 25 | 163% | 0.29× |
| 6 | 256 | ≥1 | 685 | 70 | 494 | 25 | 105% | 0.07× |
| 7 | 128 | ≥1 | 353 | 11 | 248 | 25 | 53% | 0.02× |
Seven images, representing an identical tissue area of 775 × 775 µm, were acquired using a 20×/0.7 NA objective lens with varying sampling rates. Images were acquired stepwise with an ∼4-fold change in pixel area at each step. For every frame size, the lower limit of the particle size was defined according to the micrometer/pixel size of the image, and the cutoff was set at 2 µm where applicable. Line 4 represents the optimal lateral resolution, based on the structures of interest. Column A, Sampling rate shown as frame size; column B, particle size used for quantification; columns C–E, quantification results across several background processing iterations [column C, original image, no processing; column D, application of a median filter (radius = 2); column E, application of the proposed method]; column F, sigma radius values for the “generate blurred image” step; column G, percentage of counts in column E compared with the highest resolution image (line 1, column E); column H, difference in file size compared with the optimized setting. Note the increase in false counts with inappropriate processing when pixel size approaches target structure size.