Maximum Likelihood Localization Maps

Single-molecule localization microscopy commonly reconstructs images from estimated emitter coordinates. We calculate maximum-likelihood localization maps (MLLM), a non-iterative approach that evaluates positional likelihood from measured data and a supplied point-spread function. The MLLM of each detected single molecule image is added into a final upsampled image representing the overall molecular probability map, preserving the positional likelihood structure and obviating separate coordinate-based rendering. MLLM calculation is noniterative, fast, supports any calibrated point-spread function, accounts for local background variation, supports two- and three-dimensional reconstruction, and can be calculated in parallel.