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Imagej auto threshold7/21/2023 ![]() In the Color Threshold dialog, they are applied exclusively to the Brightness channel of your 24-bit color image. Manders’ tM2 (Above autothreshold of Ch1): 0.591Ĭan anyone figure out why I have the warning message though I subtracted background and selected ROI for calculation? And I am not sure if Pearson’s R value (above threshold): 0.31 is too low? I also tried using 8-bit binary mask but it was even worse.Īny help is much appreciated. The auto-threshold methods in the Threshold dialog all are algorithms working on single channel (8-bit or 16-bit) images. Manders’ tM1 (Above autothreshold of Ch2): 0.773 Manders’ M2 (Above zero intensity of Ch1): 0.982 Manders’ M1 (Above zero intensity of Ch2): 1.000 Pearson’s R value (above threshold): 0.31 Pearson’s R value (below threshold): 0.00 This might not affect Pearson’s correlation values very much, but might harm Maybe do a background subtraction in both channels. Threshold the image using range of 0 to value (2) as measured above to get the Thresholded Image. Significant positive or negative zero offset in the image data intensities. Easy to achieve, and seems reasonably logical. This means the y-intercept is far from zero, implying a from fiji.threshold import AutoThreshold imp IJ.getImage() hist imp.getProcessor().getHistogram() lowTH AutoThreshold.Otsu(hist) print lowTH if you want to convert to mask, then imp.getProcessor().threshold(lowTH) For the other algorithms for the automatic threshold value estimation, see the Javadoc. Line to the mean value of Channel 2 is high. ![]() Warning! y-intercept far from zero - The ratio of the y-intercept of the auto threshold regression
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