Automatic Quantification of Fluorescence from Clustered Targets in Microscope Images
A cluster of fluorescent targets appears as overlapping spots in microscope images. By quantifying the spot intensities and locations, the properties of the fluorescent targets can be determined. Commonly this is done by reducing noise with a low-pass filter and separating the spots by fitting a Gaussian mixture model with a local optimization algorithm. However, filtering smears the overlapping spots together and lowers quantification accuracy, and the local optimization algorithms are uncapable to find the model parameters reliably. In this sudy we developed a method to quantify the overlapping spots accurately directly from the raw images with a stochastic global optimization algorithm. To evaluate the method, we created simulated noisy images with overlapping spots. The simulation results showed the developed method produced more accurate spot intensity and location estimates than the compared methods. Microscopy data of cell membrane with caveolae spots was also succesfully quantified with the developed method.
KeywordsMixture Model Gaussian Mixture Model Point Spread Function Spot Intensity Population Member
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