Intelligent Medical Image Viewing Engine for Rapid Browsing
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Solution Overview
Problem
Current medical imaging viewer systems organize images based on the time of acquisition, which is not optimal for viewing images relevant to specific diseases or measurements, requiring clinicians to traverse through numerous images to find relevant data.
Innovation Solution
An intelligent medical image viewing engine that automatically detects the type and viewpoint of images within an image series, enabling filtering, sorting, and searching by attributes associated with diseases and measurements of interest, allowing clinicians to quickly identify and view relevant images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If images are organized by time of acquisition, then chronological order is maintained, but clinicians must traverse through numerous images to find relevant data
Solution Approach 1:
The patent segments the image set by organizing images into multiple groups based on different attributes (anatomy, pathology, imaging modality, etc.) rather than presenting a single chronological sequence. This allows clinicians to access specific segments relevant to their diagnostic needs without traversing the entire image set.
Solution Approach 2:
The patent adds organizational dimensions beyond time by introducing multiple attribute-based sorting criteria. Images can be organized by anatomical region, pathological findings, imaging modality, or other clinically relevant attributes, creating a multi-dimensional organization system that enables direct access to relevant images.
2Loss of information
If all images are displayed, then complete information is available, but browsing efficiency decreases
Solution Approach 1:
The patent extracts and highlights key organizational attributes from the image metadata (such as anatomy, pathology, modality) and uses these extracted features to automatically organize and prioritize image display. This extraction enables the system to present only the most relevant images first while maintaining access to the complete set.
Solution Approach 2:
The system performs preliminary organization of images based on multiple attributes before the clinician views them. Images are pre-sorted and grouped according to clinically relevant criteria, so that when the clinician accesses the image set, the most relevant images are already positioned for easy access without requiring manual browsing.
3Adaptability or versatility
If manual sorting by clinicians is required, then customization is possible, but time and effort increase
Solution Approach 1:
The system provides self-service organization by automatically sorting and grouping images based on their metadata attributes without requiring manual intervention from the clinician. The intelligent organization occurs autonomously, yet remains adaptable to different clinical needs through multiple pre-configured organizational schemes.
Solution Approach 2:
The patent changes the organizational parameters from单一的 time-based sorting to multiple attribute-based parameters (anatomy, pathology, modality, etc.). This parameter transformation enables the system to adaptively organize images according to different clinical contexts without manual reconfiguration, as the same image set can be reorganized by different attributes instantaneously.
Data Source
AI summary
A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to specifically configure the processor to implement an intelligent medical image viewing engine. The intelligent medical image viewing engine receives a medical imaging study data structure comprising a plurality of electronic medical images from a medical image database. An image processing component executing within the intelligent medical image viewing engine analyzes the medical imaging study data structure to identify, for each electronic medical image in the plurality of electronic medical images, a corresponding set of image attributes. The intelligent medical image viewing engine receives a user input specifying at least one filter attribute for generating a medical image output and correlates the at least one filter attribute with at least one medical attribute of medical images to be used for selection of electronic medical images from the medical imaging study data structure. An image selection component executing within the intelligent medical image viewing engine selects a subset of the electronic medical images in the plurality of electronic medical images based on the correlation of the at least one filter attribute with the at least one medical attribute. A user interface generation component executing within the intelligent medical image viewing engine generates and outputs a medical image output comprising the subset of electronic medical images based on the selection.