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Extracting data from pictures of medical records is a common task in the insurance industry, especially with the increased use of smartphone cameras for data acquisition. However, challenges persist due to poor image quality and complex document layouts. To address this, a mixed initiative pipeline is proposed for extracting data from medical invoices, integrating deep learning-based automatic prediction models with user interventions. In the table detection phase, users draw a quadrangle to identify target areas and lines to distinguish header cells. During the structure recognition stage, an automated model suggests line placements, which users can refine using simple click-and-drag actions. Finally, in the template matching stage, users select from the top five suggested templates.