PixelGuard is dedicated to medical image de-identification. Our algorithm is driven by a robust combination of artificial intelligence and image processing techniques. The proposed method offers up to 72% compression in comparison to the original DICOM files. Not only does this have implications for the long-term storage of these large files, but it also allows for substantially increased short-term storage for applications in machine learning (i.e., batch processing). We developed this with the goal of creating a disruptive technology to assist research institutions and health systems disseminate data to better leverage insights from medical image data for machine learning and artificial intelligence. Of note, this software is currently being leveraged by the NIH-funded study HeartShare.