Lung Calcification Detection Using Breed and Age Data
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Solution Overview
Problem
Existing medical care technologies face challenges in accurately detecting lung calcification from medical images, which can lead to inadequate detection of lung diseases, especially when calcification is not properly identified.
Innovation Solution
A medical care support device and method that acquires medical image data, breed information, and age information to derive the degree of lung calcification using a learned model, and outputs warning information or examination items based on correspondence relationships, allowing for effective medical care support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If calcification of the lung is detected from medical image alone, then detection process is simple, but detection accuracy deteriorates when calcification cannot be properly discriminated
Solution Approach 1:
The patent transitions from two-dimensional medical image analysis to three-dimensional volumetric analysis by acquiring CT images at multiple thickness positions and performing three-dimensional reconstruction. This dimensional expansion enables more accurate discrimination of calcification from other lung abnormalities, resolving the contradiction between simple detection and accurate detection.
Solution Approach 2:
The patent changes the parameter of analysis from single-image visual inspection to quantitative three-dimensional volume measurement of calcification. By calculating the volume of calcified portions through three-dimensional reconstruction, the system achieves objective and accurate detection that overcomes the subjectivity and inaccuracy of traditional two-dimensional image analysis.
2Measurement precision
If age and breed information are incorporated into calcification assessment, then diagnostic accuracy improves, but system complexity increases
Solution Approach 1:
The patent creates a universal assessment system that integrates multiple functions: three-dimensional calcification volume measurement, age-related reference value comparison, and breed-specific norm evaluation. This multi-functional system handles diverse assessment requirements through a unified approach, improving diagnostic accuracy while managing complexity through systematic integration.
Solution Approach 2:
The patent performs preliminary actions by pre-establishing reference tables containing age-appropriate and breed-specific normal calcification ranges. These reference values are prepared in advance, allowing the system to quickly compare individual patient measurements against appropriate norms without requiring complex real-time calculations, thus improving accuracy while controlling system complexity.
Data Source
AI summary
A medical care support device includes: an acquisition unit that acquires medical information including medical image data representing a medical image obtained by capturing a lung of a subject, breed information representing a breed of the subject, and age information representing an age of the subject when the medical image is captured; and a derivation unit that derives a degree of calcification of the lung of the subject based on the medical information acquired by the acquisition unit and a learned model learned in advance using a plurality of pieces of learning medical information including medical image data representing a medical image in which a label is assigned to a calcified portion of the lung, the breed information, and the age information.