Medical Image Processing for Pleural Adhesion Assessment
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Solution Overview
Problem
Current medical image processing technologies face challenges in accurately assessing adhesion between the parietal and visceral pleura, particularly in areas where ultrasound waves cannot reach, leading to potential delays in medical intervention due to incorrect assessments.
Innovation Solution
An image processing apparatus that calculates an index of adhesion by analyzing mobility information across temporal phases using classification information to determine the state of adhesion between regions, allowing for precise evaluation of conglutination even in areas inaccessible to ultrasound waves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ultrasound waves are used to assess adhesion between pleura, then the assessment can be performed in real-time during surgery, but the assessment is inaccurate in areas where ultrasound waves cannot reach
Solution Approach 1:
The patent transitions from two-dimensional ultrasound imaging to three-dimensional CT image data, enabling assessment of adhesion in areas inaccessible to ultrasound waves. The processing circuitry generates three-dimensional images from CT data taken at multiple time points, providing comprehensive spatial coverage that overcomes the limited penetration and coverage area of ultrasound waves.
Solution Approach 2:
The patent replaces the mechanical ultrasound wave-based assessment system with a computational image processing system. Instead of relying on physical ultrasound wave propagation through tissues, the system uses processing circuitry to analyze CT image data and calculate adhesion indices, eliminating the coverage limitations of acoustic wave propagation.
2Device complexity
If adhesion assessment is performed using conventional methods, then the process is simple, but delays in medical intervention occur due to incorrect assessments
Solution Approach 1:
The patent performs adhesion assessment using CT images taken at multiple time points before surgical intervention. By calculating the adhesion index in advance based on mobility information from sequential CT scans, the system provides accurate assessment results that guide surgical planning, preventing delays caused by intraoperative discovery of incorrect assessments.
Solution Approach 2:
The system uses processing circuitry to calculate mobility information of image data between different time points, providing feedback on adhesion states. This quantitative feedback mechanism enables accurate differentiation between adhered and non-adhered regions, improving assessment reliability compared to conventional subjective methods.
Data Source
AI summary
An image processing apparatus includes processing circuitry configured: to obtain a plurality of images taken so as to include a target site of a subject in temporal phases; and to calculate an index indicating a state of an adhesion at a boundary between a first site of the subject corresponding to a first region and a second site of the subject corresponding to a second region, by using classification information used for classifying each of pixels into one selected from between a first class related to the first region and a second class related to a second region positioned adjacent to the first region in a predetermined direction, on a basis of mobility information among the images in the temporal phases with respect to the pixels in the images that are arranged in the predetermined direction across the boundary between the first region and the second region of the images.