Dynamic Chest Imaging for Low-Radiation Pleural Adhesion Detection
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Solution Overview
Problem
Existing medical imaging technologies for detecting pleural adhesion, such as CT devices and ultrasound diagnostic apparatuses, are costly, complex, and expose patients to high radiation, making them unsuitable for routine use before surgery, while techniques relying on diaphragm shape changes fail to detect all adhesions.
Innovation Solution
A dynamic image analysis apparatus that uses a hardware processor to generate information on pleural adhesion based on motion amounts in lung regions, including or excluding the rib cage, through dynamic imaging by radiation, and outputs this information using an outputter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CT device or 4D-CT is used to detect pleural adhesion, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent uses ordinary X-ray imaging equipment to create a simplified copy of the complex 4D-CT functionality. Instead of requiring expensive 4D-CT scanners, the invention captures standard dynamic X-ray images and extracts motion information through image processing algorithms, achieving comparable adhesion detection capability with simpler, more accessible equipment
Solution Approach 2:
The patent replaces the mechanical complexity of specialized 4D-CT imaging systems with a computational approach. By substituting hardware complexity with software-based motion analysis of standard X-ray images, the system achieves pleural adhesion detection without requiring complex imaging machinery
2Measurement precision
If CT device or 4D-CT is used to detect pleural adhesion, then measurement precision is improved, but radiation exposure increases
Solution Approach 1:
The patent uses partial action by capturing only essential dynamic X-ray images at key respiratory phases rather than continuous imaging. This selective imaging approach reduces overall radiation exposure while still providing sufficient motion information to detect pleural adhesion through the motion vector analysis of lung surface displacement
3Area of stationary object
If ultrasound diagnostic apparatus is used to image entire subject, then measurement coverage is improved, but imaging time increases significantly
Solution Approach 1:
The patent employs periodic action by capturing X-ray images at specific, periodic intervals corresponding to respiratory cycles (inhaling and exhaling phases). This periodic sampling captures the necessary motion information for adhesion detection without requiring continuous imaging of the entire subject, thus reducing imaging time while maintaining detection accuracy
4Area of stationary object
If ultrasound diagnostic apparatus is used to image entire subject, then measurement coverage is improved, but device operation difficulty increases
Solution Approach 1:
The patent leverages the universality of ordinary X-ray imaging equipment, which is already widely available in medical facilities. By using this existing multi-functional equipment for both standard imaging and pleural adhesion detection through dynamic image analysis, the system avoids the need for specialized ultrasound apparatus and complex imaging procedures
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and low-radiation detection of pleural adhesion, avoiding the need for expensive and complex equipment, and allowing easy identification of adhesion locations and degrees in a typical medical facility.
Implementation Method 1
a dynamic image of a chest portion obtained by dynamic imaging by radiation
Data Source
AI summary
A dynamic image analysis apparatus includes a hardware processor, and an outputter. The hardware processor obtains a dynamic image of a chest portion obtained by dynamic imaging by radiation. The hardware processor performs a first generating process in which information regarding pleural adhesion is generated based on a motion amount in a region including at least a region adjacent to a rib cage in a lung region in the dynamic image. The outputter outputs the generated information regarding the pleural adhesion.


