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In traditional photon counting imaging and centroiding with simple one-iteration algorithms, it is usually ensured that the frames do not contain images of photons that have any overlap. However, in biological imaging with super-resolution microscopy the image acquisition speed is a critical parameter which can be shortened by imaging as many molecules as possible in each frame. While simple one-iteration center-of-mass algorithms are not capable of guessing which proportion of the detected intensity in a pixel that contains overlapping intensity from more than one photon belongs to which photon event, the separation of overlapping events is possible with algorithms that fit several point-spread functions to an area containing overlapping events. ThunderSTORM's option for Multi-emitter Fitting Analysis (MFA) produces excellent results with recognising and separating overlapping EBCCD photon events, as shown in Fig~\ref{fig_mfa}.