Secure Medical Image Upload via Pre-Upload Metadata De-identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for analyzing and communicating medical imaging data, particularly in cancer diagnosis, lack effective automation and patient-friendly communication of results, leading to potential misinterpretation and increased patient trauma due to complex information.
Innovation Solution
A system and method for secure upload of medical images and metadata to a cloud-based platform, utilizing a graphical user interface to de-identify sensitive data elements before upload, ensuring patient privacy and facilitating intuitive data review and upload processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If medical images and metadata are uploaded to cloud-based platforms for analysis, then data analysis capability and communication efficiency are improved, but patient privacy and data security are compromised due to exposure of sensitive information
Solution Approach 1:
The system performs de-identification of sensitive metadata elements before upload to the cloud platform. The graphical user interface allows users to review and control which data elements are removed or masked in advance, ensuring patient privacy is protected while still enabling cloud-based analysis of the medical images.
Solution Approach 2:
The system extracts and removes sensitive data elements from the metadata associated with medical images before uploading to the cloud platform. This separation allows the medical image data to be analyzed in the cloud while the sensitive patient information remains on the local device or is completely removed.
2Productivity
If automated analysis tools are implemented for medical imaging data, then analysis efficiency and objectivity are improved, but complexity of the system and difficulty of operation increase
Solution Approach 1:
The graphical user interface enables users to independently control the de-identification process by reviewing metadata elements and selecting which data to remove or mask. This self-service approach allows users to customize their privacy preferences without requiring complex configuration or expert knowledge.
Solution Approach 2:
The system divides the metadata into identifiable data elements that can be individually reviewed and controlled. The graphical interface presents metadata in a structured format, allowing users to selectively manage different types of information (e.g., patient identifiers, study details) separately.
3Adaptability or versatility
If cloud-based platforms are used for medical image analysis, then collaboration and communication of results are improved, but control over sensitive data is reduced
Solution Approach 1:
Users perform de-identification and review of metadata before uploading to the cloud platform. This preliminary control ensures that sensitive information is removed or masked according to user preferences before leaving the local device, maintaining data control while enabling cloud-based collaboration.
Data Source
AI summary
Presented herein are systems and methods that facilitate user review and uploading of files comprising medical images and associated metadata from a local computing device to a network-based image analysis and/or decision support platform. The systems and methods described herein allow image upload to be performed in a secure fashion that prevents the network-based platform from accessing sensitive data as it is prepared for upload. Prior to file upload, sensitive data elements are flagged and their values removed and/or masked. Notably, the approaches described herein provide intuitive graphical user interface (GUI) tools that allow a user, such as a medical practitioner or researcher, to review not only the images and metadata in the files that they plan to upload, but also to review and control the process by which sensitive data elements are removed and/masked, thereby confirming that all files are free of sensitive information prior to upload.