Multi-Modality Medical Image Workflow Guidance Algorithm
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cardiovascular imaging and information systems (CVIS) face challenges in efficiently managing and comparing multi-modality medical images due to the large number of images and complexity of cardiovascular anatomy, leading to time-consuming manual steps for clinicians.
Innovation Solution
A computer-implemented method and system for multi-modality medical image clinical workflow guidance, utilizing a clinical-concept-to-medical-image linking algorithm to assess user input and provide indications for clinical workflow guidance, thereby improving efficiency and accuracy in image comparison and interpretation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If clinicians manually query and arrange multi-modality medical images, then they can access comprehensive imaging data, but the process becomes time-consuming and energy-intensive
Solution Approach 1:
The system automatically queries, retrieves, and arranges multi-modality medical images based on clinical concepts without requiring manual clinician intervention. The algorithm autonomously performs image selection, spatial alignment, and temporal synchronization, allowing the system to serve itself rather than requiring continuous human operation for each imaging workflow.
Solution Approach 2:
The patent replaces the manual mechanical process of image querying and arrangement with an automated clinical-concept-to-medical-image linking algorithm. This algorithmic system substitutes human clinicians' manual operations with computational processes that automatically retrieve and organize images from multiple modalities based on clinical concepts.
2Measurement precision
If clinicians manually align images across different modalities, then spatial and temporal accuracy is achieved, but the complexity of the workflow increases
Solution Approach 1:
The patent introduces a clinical-concept-to-medical-image linking algorithm as an intermediary between clinical concepts and multi-modality images. This intermediary automatically handles the complex tasks of image querying, retrieval, spatial alignment, and temporal synchronization, transforming the complex manual workflow into an automated process that maintains precision without requiring clinician expertise in image alignment techniques.
3Loss of information
If multiple manual steps are performed for image retrieval and arrangement, then comprehensive image comparison is enabled, but productivity decreases
Solution Approach 1:
The system performs preliminary automated actions by pre-querying and pre-arranging multi-modality images based on clinical concepts before the clinician begins interpretation. The algorithm proactively retrieves relevant images from multiple modalities and automatically aligns them in the viewport, so that when the clinician reviews the case, the images are already organized and ready for comparison, eliminating the need for manual preparation steps.
Data Source
AI summary
A computer-implemented method for multi-modality medical image clinical workflow guidance comprises a step of receiving a user input (306-4) in relation to a first medical image data set (306-2) acquired by means of a first medical imaging modality (304-A). By means of a clinical-concept-to-medical-image linking algorithm (314), the received user input (306-4) is assessed in view of at least one second medical image data set (308-1) acquired by means of at least one second medical imaging modality (304-B). An indication of a clinical workflow guidance in relation to the at least one second medical image data set (308-1) is output.