Automatic 3D Cardiac Model Generation from Multi-Modality Images
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Solution Overview
Problem
Current methods for merging medical image datasets from different modalities, such as heart ultrasound and nuclear magnetic resonance tomographies, require manual processing by doctors, leading to errors and increased workload, which can be life-threatening in diagnostics and therapy planning.
Innovation Solution
A computer-implemented method and device that automatically creates and merges three- or four-dimensional models from patient-specific medical image datasets across various modalities, using contour lines and semi-automatic fitting to integrate data from different sources, providing a graphical user interface for presentation and editing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual merging of image datasets is performed by doctors, then comprehensive diagnostic analysis can be achieved, but error rate increases and diagnostic efficiency decreases
Solution Approach 1:
The system enables automatic self-service merging of image datasets through computational algorithms that autonomously integrate data from multiple modalities without requiring manual doctor intervention, thereby reducing errors while maintaining comprehensive analysis capabilities
Solution Approach 2:
The patent replaces the manual mechanical process of doctor-based image merging with an automated computational system that uses algorithms and software to perform the integration, eliminating human error while preserving diagnostic thoroughness
2Loss of information
If multiple image datasets from different modalities are collected, then comprehensive diagnostic information is obtained, but data integration complexity increases
Solution Approach 1:
The patent implements a unified integration platform that combines multiple image datasets from different modalities into a single coherent model, managing complexity through standardized processing pipelines that handle diverse data types systematically
Solution Approach 2:
The system introduces an intermediary integration layer that standardizes and harmonizes data from various modalities before final synthesis, acting as a mediator that simplifies the complexity of direct multi-modal data integration while preserving all diagnostic information
3Productivity
If automated model creation is implemented, then diagnostic efficiency improves, but automation extent must be balanced with medical expertise requirements
Solution Approach 1:
The system implements self-service automated model creation that handles routine integration tasks autonomously, freeing medical professionals to focus on high-level diagnostic interpretation while maintaining high automation levels for data processing operations
Data Source
AI summary
At least one embodiment of the present invention relates to a method, a device and/or a computer program product for creating a (three- or four-dimensional) model from a number of different image datasets from a number of modalities. To this end, in at least one embodiment, the image datasets are fitted into a representation provided, the different image datasets being automatically enriched with contour lines and integrated into the representation. The model is created from this.