Cloud Medical Image Processing Gesture Mapping and PHI Segregation
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Solution Overview
Problem
Cloud-based image processing systems for medical images face challenges in ensuring data confidentiality, particularly for Protected Health Information (PHI), and require user-specific gestures that are not seamlessly compatible across different medical devices from various vendors, leading to errors and inefficiencies.
Innovation Solution
A method and system that utilize an extended touch screen device to receive user input configurations, segregate and encrypt PHI data, and map user-specific gestures to standard gestures, enabling secure and intuitive image processing across cloud-based applications while maintaining compatibility with different medical devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If cloud-based image processing is used to improve accessibility and collaboration, then data confidentiality and security are compromised
Solution Approach 1:
The system segments data into two categories: PHI (protected health information) and non-PHI data. PHI data remains encrypted and stored locally on the client device, while only non-PHI data is transmitted to the cloud for processing. This segmentation allows cloud-based accessibility while maintaining confidentiality of sensitive information through selective data separation and encryption.
2Ease of operation
If user-specific gestures are supported to improve user experience, then compatibility across different vendor systems deteriorates
Solution Approach 1:
The system introduces a gesture mapping layer that acts as an intermediary between user-specific gestures and standard DICOM gestures. This mapping layer translates vendor-specific or custom gestures into standardized DICOM commands, enabling users to maintain their preferred gesture patterns while ensuring compatibility across different cloud-based image processing systems from various vendors.
Data Source
AI summary
A method and system are a for gesture support system for controlling a cloud-based image processing application. In an embodiment, the system includes an extended touch screen device; a DICOM Appliance including a receiver and an uploader client, adapted for segregating PHI-data and non-confidential image data, and for encrypting PHI-data and sending a data package, including the encrypted PHI-data and non-confidential image data to a cloud server. The cloud server is adapted for processing the medical image data. It receives the data package form the uploader client and decrypts the received data package. A gesture reception unit receives user-specific gesture signals and a mapping unit maps the received user-specific gesture signals to standard gestures and provides the standard gestures to the cloud server for generating control instructions for the image processing.