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Injury to the heart results in recruitment of immune cells to the damaged site where they are required for repair and regeneration. To determine the specific functions of immune cells following injury to the heart it would be ideal to visualise and track their migration to the damaged region in vivo but this is technically challenging due to the rapid movement of the heart. Using zebrafish as a model, we acquired images of fluorescently labelled cells in a live, beating heart using multiphoton or lightsheet microscopes. Once acquired, these images needed to be both temporally and spatially aligned to control for the movement of the heart. During this project we designed and built software and an image analysis pipeline to automate this alignment process. The aligned datasets can then be used to evaluate cell population evolution over time using segmentation as means to isolate cell groups.