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In traditional photon counting imaging 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 the separation of overlapping events is not possible with simple one-iteration centre-of-mass algorithms, algorithms that fit a PSF to the event can potentially resolve overlapping events by fitting multiple PSFs to a region 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}. For the low density USAF data containing an average of 150 photons / frame the photon count increases 2\% with MFA enabled, and for higher density cell data containing an average of 460 photons / frame the photon count increases 13\%. Fitting of multiple PSFs is time-consuming and the processing time increases significantly with MFA enabled, as expected. However, for biological imaging the image acquisition time is a critical parameter, and the separation of overlapping events can potentially lead to significant reduction in image acquisition times.