Cross-Referenced Diagnostic Image Database System
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Solution Overview
Problem
Medical professionals, particularly in visually centered specialties, face challenges in diagnosing and identifying diseases due to limited access to relevant visual information and insufficient tools for pattern recognition, leading to delayed or inaccurate diagnoses.
Innovation Solution
A system and method that cross-references an image database with a knowledge database, allowing users to input descriptive characteristics of a sample, and uses a diagnostic engine to identify a subset of possible diagnoses, reorganizing the image database for concurrent presentation of relevant images for user review, thereby aiding in the diagnostic process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If paper-based atlases are used for diagnostic reference, then visual information is available, but access speed is slow and information retrieval is inefficient
Solution Approach 1:
The patent replaces the mechanical system of manually flipping through paper-based atlases with a computer-driven interface that provides electronic access to diagnostic images. This substitution enables near instantaneous retrieval of visual information through digital databases, eliminating the time-consuming manual search process while maintaining comprehensive visual reference capabilities.
Solution Approach 2:
The patent creates digital copies of diagnostic images and organizes them in electronic databases that can be rapidly accessed and displayed. These digital replicas allow users to view diagnostically relevant images immediately on computer screens, replacing the need to physically handle and search through paper-based atlases, thereby significantly reducing access time.
2Reliability
If comprehensive image databases are created to improve diagnostic accuracy, then more visual information is available, but system complexity increases
Solution Approach 1:
The patent segments the comprehensive image database into organized categories and subsets based on diagnostic relevance. The system divides the large database into manageable sections that can be selectively accessed based on the specific diagnostic query, making the complex information structure easier to navigate while maintaining comprehensive coverage for accurate diagnosis.
Solution Approach 2:
The patent introduces a diagnostic engine as an intermediary between the user and the comprehensive image database. This engine automatically processes user inputs, searches the database, and retrieves relevant images, thereby simplifying the interaction with the complex database structure while ensuring accurate and comprehensive diagnostic information is provided.
3Productivity
If manual search methods are used to find diagnostic images, then all images are accessible, but information retrieval is time-consuming
Solution Approach 1:
The patent implements a feedback mechanism where the diagnostic engine continuously refines search results based on user interactions and diagnostic criteria. The system analyzes user inputs, retrieves relevant images, and provides feedback that helps narrow down or expand the search based on diagnostic relevance, ensuring that the most appropriate images are retrieved efficiently without losing potentially important information.
Solution Approach 2:
The patent performs preliminary organization and tagging of images in the database with diagnostic metadata and relevance indicators before user queries are submitted. This preliminary action enables the diagnostic engine to quickly filter and retrieve only the most relevant images based on user inputs, significantly accelerating information retrieval while ensuring high diagnostic relevance.
Data Source
AI summary
The present invention is a method and apparatus for increasing the usefulness of visual knowledge in a number of applications. It distills the relationships between characteristics and hypotheses into database form, thereby organizing visual information in a manner suitable to aid the user in the investigation of the various hypotheses (medical diagnosis, pill identification, plant/animal identification, cause of death, cause of accident, etc.). The invention sidesteps unresolved issues around knowledge engineering by not automating a decision making process. Rather, the present invention utilizes a relational database to dynamically respond to textual and visual findings as an aid to assist a user reaching a reasoned conclusion based upon information available by direct observation and comparison with stored image and textual data.