To the Editor: Although conventional microscopes have a resolution limited by diffraction to about half the wavelength of light, several recent advances have led to microscopy methods that achieve roughly tenfold improvements in resolution. Among them, photoactivated light microscopy (PALM) and stochastic optical resolution microscopy (STORM) have become particularly popular, as they only require relatively simple and affordable modifications to a standard total internal reflection fluorescence (TIRF) microscope1–3 and have been extended to three-dimensional (3D) super-resolution and multicolor imaging4, 5. PALM and STORM achieve super-resolution by sequentially imaging sparse subsets of photoswitchable molecules. Positions of individual molecules are computed from individual low-resolution images with subdiffraction accuracy. These positions are then corrected for drifts and subsequently assembled into one or more super-resolution images. Unfortunately, in most current implementations, this reconstruction may take from several hours to days for a single dataset, thus forbidding visual inspection of super-resolution images in real time. Additionally, PALM and STORM software used to date is generally not freely available, strongly limiting the adoption of this otherwise relatively simple microscopy method. Two recent publications independently demonstrated two-dimensional (2D) algorithms for realtime PALM and STORM reconstructions6, 7. Here we present QuickPALM (Supplementary Software 1), a freely available and open-source algorithm as a plugin for the widely used ImageJ (http://rsb. info. nih. gov/ij/) software that combines real-time processing capability with additional important features including 3D reconstruction, drift correction and real-time acquisition control (http://code. google. com/p/quickpalm/). PALM and STORM reconstruction algorithms usually rely on ‘fitting’Gaussian kernels to detected diffraction-limited spots. Although they permit high-accuracy localizations, these iterative methods can require up to several hours of processing time. We have developed a high-speed reconstruction algorithm that uses the classical Högbom ‘CLEAN’method8 for spot finding, followed by a modified center of mass algorithm to compute the spot position and parameters defining spot shape along the hori-10 particles per frame

100 particles per frame