Thoracic Diagnosis System Using Lung Field Segmentation and Ratio Histograms
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Solution Overview
Problem
Conventional methods for diagnosing thoracic movements using dynamic images struggle to provide clinical features effectively for physicians without extensive experience, as they rely on calculating maximum, average, or intermediate values of pixel differences, which are difficult to interpret.
Innovation Solution
A thoracic diagnosis assistance system that images chest movements, extracts the lung field region, divides it into sub-regions, correlates these regions across frames, calculates inspiratory and expiratory feature quantities, and displays a histogram of their ratio to facilitate clinical feature analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If maximum/average/intermediate values of pixel differences are calculated from dynamic images, then processing is simplified, but clinical features become difficult to grasp for physicians
Solution Approach 1:
The lung field region is divided into multiple sub-regions, and each sub-region is independently analyzed to calculate inspiratory and expiratory feature quantities. This segmentation allows detailed local analysis while providing comprehensive clinical information through histogram display of ratio values across all sub-regions.
Solution Approach 2:
The patent introduces an intermediary processing layer that calculates ratio values of inspiratory to expiratory feature quantities for each sub-region, then displays these ratios as a histogram. This intermediary transformation converts complex pixel difference data into clinically interpretable visual information that bridges the gap between raw data and diagnostic understanding.
2Measurement precision
If dynamic imaging is performed to capture chest movements, then diagnostic information is obtained, but the complexity of analyzing ventilation features increases
Solution Approach 1:
The lung field is segmented into multiple sub-regions, allowing independent analysis of ventilation characteristics in different areas. This segmentation simplifies the overall analysis by breaking down the complex lung field into manageable units that can be processed systematically.
Solution Approach 2:
The patent transforms the analysis from raw pixel difference values to normalized ratio parameters (inspiratory feature quantity / expiratory feature quantity). This parameter transformation simplifies the data characteristics and makes ventilation features more easily quantifiable and comparable across different sub-regions and patients.
Data Source
AI summary
Provided is a thoracic diagnosis assistance system. The system includes, an imaging unit, an extracting unit, a region dividing unit, an analysis unit and a display unit. The extraction unit extracts a lung field region from the plurality of successive image frames generated by the imaging unit. The region dividing unit divides the lung field region extracted by the extraction unit into a plurality of sub-regions and correlates the sub-regions among the plurality of image frames. The analysis unit performs an analysis of the sub-regions to calculate an inspiratory feature quantity and an expiratory feature quantity and to calculate a value of a ratio of the calculated inspiratory feature quantity to expiratory feature quantity and creates a histogram of the calculated ratio value. The display unit displays the histogram.