Cloud-Based PACS Integration for AI Medical Image Analysis
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Solution Overview
Problem
Existing Picture Archiving and Communication Systems (PACS) struggle to process computationally-intensive AI algorithms for medical image analysis, requiring expensive dedicated hardware and lacking a platform to manage and support AI-based analysis for medical imaging data.
Innovation Solution
A cloud-based data distribution and analysis system that receives medical image data from PACS, processes it using machine learning models hosted by a computing service, generates additional biometric data, and incorporates it into electronic health records, allowing for efficient AI-based analysis without significant upfront hardware costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If AI algorithms are processed on-site using dedicated hardware, then processing capability is improved, but hardware cost increases significantly
Solution Approach 1:
The patent introduces a cloud computing service as an intermediary between the PACS system and AI algorithms. Instead of requiring expensive dedicated hardware at the radiology department, the system uses cloud-based computing resources to host and execute AI models. The cloud service acts as a mediator that provides computational power on-demand, eliminating the need for costly on-site hardware while maintaining processing capability.
Solution Approach 2:
The patent implements a software-based AI algorithm interface that can be deployed across multiple cloud instances. Rather than requiring physical dedicated hardware at each location, the system creates virtual copies of the AI processing capability through software deployment on cloud platforms. This allows multiple radiology departments to access the same AI algorithms without each needing expensive dedicated equipment.
2Device complexity
If existing PACS systems are used without additional hardware, then system simplicity is maintained, but AI processing capability is insufficient
Solution Approach 1:
The patent creates a universal interface layer that enables existing PACS systems to work with cloud-based AI algorithms without requiring hardware changes. The same PACS infrastructure can serve both traditional imaging functions and AI processing by connecting to the cloud service. This multi-functional approach allows the system to maintain simplicity while gaining advanced AI capabilities through the universal cloud interface.
3Ease of manufacture
If cloud-based computing services are used, then hardware cost is reduced, but data transmission and processing time may increase
Solution Approach 1:
The patent implements preliminary actions by pre-loading AI models and necessary processing components onto the cloud platform before actual image analysis is needed. The system establishes pre-configured data transmission channels and pre-processes model parameters so that when images arrive, they can be processed with minimal delay. This preparation phase reduces the actual processing time despite the cloud-based architecture.
Data Source
AI summary
Data distribution and analysis systems, and associated methods are described herein. In one aspect, a method for distributing data can include: receiving, by a computing service and from a medical data server, medical image data stored by the PACS; inputting the medical image data into a machine learning model hosted by the computing service, wherein the computing service allows users to upload machine learning models and configure corresponding machine learning models to interface with the medical data server; generating, by the machine learning model, additional biometric data corresponding to the medical image data; and sending the additional biometric data to the medical data server, wherein the additional biometric data and the medical image data is incorporated into an electronic health record (EHR).