Journal of Microscopy, Vol. 257, Issue 3 2015, pp. 226–237 doi: 10.1111/jmi.12205 Received 25 March 2014; accepted 14 November 2014 Background intensity correction for terabyte-sized time-lapse images J. CHALFOUN ∗ , M. MAJURSKI ∗ , K. BHADRIRAJU †, S. LUND ∗ , P. BAJCSY ∗ & M. BRADY ∗ ∗ Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, U.S.A. †Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, U.S.A. Key words. Background modelling, fluorescent image correction, image mosaic, large field of view. Summary Several computational challenges associated with large-scale background image correction of terabyte-sized fluorescent im- ages are discussed and analysed in this paper. Dark current, flat-field and background correction models are applied over a mosaic of hundreds of spatially overlapping fields of view (FOVs) taken over the course of several days, during which the background diminishes as cell colonies grow. The motiva- tion of our work comes from the need to quantify the dynamics of OCT-4 gene expression via a fluorescent reporter in human stem cell colonies. Our approach to background correction is formulated as an optimization problem over two image par- titioning schemes and four analytical correction models. The optimization objective function is evaluated in terms of (1) the minimum root mean square (RMS) error remaining after im- age correction, (2) the maximum signal-to-noise ratio (SNR) reached after downsampling and (3) the minimum execution time. Based on the analyses with measured dark current noise and flat-field images, the most optimal GFP background cor- rection is obtained by using a data partition based on forming a set of submosaic images with a polynomial surface background model. The resulting image after correction is characterized by an RMS of about 8, and an SNR value of a 4 × 4 downsam- pling above 5 by Rose criterion. The new technique generates an image with half RMS value and double SNR value when compared to an approach that assumes constant background throughout the mosaic. We show that the background noise in terabyte-sized fluorescent image mosaics can be corrected computationally with the optimized triplet (data partition, model, SNR driven downsampling) such that the total RMS value from background noise does not exceed the magnitude of the measured dark current noise. In this case, the dark current noise serves as a benchmark for the lowest noise level that an imaging system can achieve. In comparison to previous work, Correspondence to: Peter Bajcsy, Information Technology Laboratory, National In- stitute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD 20899, U.S.A. Tel: 3019752958; fax: 301-975-6097; e-mail: peter.bajcsy@nist.gov the past fluorescent image background correction methods have been designed for single FOV and have not been applied to terabyte-sized images with large mosaic FOVs, low SNR and diminishing access to background information over time as cell colonies span entirely multiple FOVs. The code is available as open-source from the following link https://isg.nist.gov/. Background Pluripotent stem cells have great potential as a source of cells for regenerative therapies. However, many aspects of control- ling pluripotent stem cells behaviour are still not well under- stood (Saha & Jaenisch, 2009). The motivation of our work comes from the need to quantify the dynamics of OCT-4 gene expression in human stem cell colonies, because OCT-4 is a critical gene in the regulation of pluripotency, or the abil- ity of stem cells to differentiate into all somatic cell types (VanDenBerg et al., 2010). OCT-4 gene expression in cells is reported by a green fluorescent protein (GFP) reporter inserted in the regulatory region of the OCT-4 gene (Zwaka & Thomson, 2003). Specifically, we are interested in understanding how colony-level GFP intensity is related to population-level cell behaviour, how normal regulation of stem cell gene expres- sion occurs, and how to develop and assess human pluripotent stem cells culture quality parameters. Time-lapse epifluorescence microscopy using fluorescent protein reporters provides an opportunity for imaging and analysing the dynamics of gene expression and morpholog- ical changes in live human pluripotent stem cells cultures. Imaging at high spatial and temporal resolutions generates terabyte-sized image sets spanning hundreds of FOVs through time (Fig. 1). There are several technical challenges to over- come before quantitative biological information can be ob- tained from these big data sets. Images of live cells, such as pluripotent stem cells, must be acquired with low-power illu- mination to minimize biological artefacts from light-induced damage to cells. Light intensity was empirically set at the low- est value, at which we could still discern image features in each Published 2014. This article is a U.S. Government work and is in the public domain in the USA