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Method and software for model-based artifact correction in time-lapse fluorescence microscopy images (Presented in CBIAS 2021 Conference in Francis Crick Institute, 22-23 November 2021) Time-lapse microscopy (TLM) is a widely used method for studying dynamic biochemical and morphological responses in biological systems. Unfortunately, fluorescence images often suffer from hardware-dependent intensity artifacts that degrade the quality of the image data. Starting from a general fluorescence image formation model, we have designed several artifact correction methods addressing the most common practical cases. The proposed techniques may correct images for XY-dependent artifacts, including excitation non-uniformity, optical vignetting, and stray light, as well as time-dependent artifacts, e.g., arising from excitation light source power variations during a time course and inherent photobleaching of cell culture medium. We have implemented these methods in a convenient open-source, cross-platform MATLAB software tool with GUI, aiming to make TLM image data more amenable for further quantitative analysis.