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extracting data from pictures of medical records is a prevalent task in the insurance industry as smartphone cameras are widely used as a data acquisition tool in everyday life however it is still challenging to fully automate the process because of poor image quality and complicated templates of the pictures therefore we propose a mixed initiative pipeline for extracting data from pictures of medical invoices where deep learning based automatic prediction models and task specific heuristics work together under the mediation of a user in the table detection stage users are required to draw one quadrangle to identify the target area and two lines to distinguish header cells from others in the table structure recognition stage automated model make suggestions of horizontal and vertical lines users can correct the horizontal and vertical border lines that define each cell through simple click drag and drop interactions in the template matching stage we had users select among top five sim