Endoscope Imaging Mask Detection Under Rapid Light Increase
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Solution Overview
Problem
In surgical endoscopes, when the distal end is close to the imaging target, imaging light can rapidly increase and reach the imaging surface beyond the boundary between the imaging and mask regions, leading to erroneous determination of mask type and decreased processing accuracy.
Innovation Solution
A medical image capturing system that includes an exposure state determination unit to recognize the correct mask type based on captured image information, allowing the processing unit to adjust settings such as light emission, focus, and gain to maintain accuracy, and a method to determine the mask type correctly even when imaging light increases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the scope is inserted close to the imaging target to improve observation detail, then imaging light rapidly increases and may reach the imaging surface beyond the mask region boundary, but this causes erroneous mask type determination and decreases processing accuracy
Solution Approach 1:
The system performs preliminary determination of the mask type based on the captured image before processing. By determining the mask type in advance using the captured image characteristics, the system can prepare appropriate processing parameters beforehand, ensuring accurate processing even when imaging light rapidly increases due to close proximity to the imaging target.
Solution Approach 2:
The system uses feedback from the captured image to determine the mask type and adjust processing parameters. By analyzing the captured image to identify the mask region boundaries and determine the appropriate mask type, the system can continuously adjust processing settings to maintain accuracy under varying lighting conditions caused by close proximity to the imaging target.
2Ease of operation
If the mask region is defined with a fixed boundary to simplify processing, then processing is easier to implement, but processing accuracy decreases when imaging light reaches beyond the boundary
Solution Approach 1:
The system dynamically determines the mask region boundaries based on the captured image rather than using fixed boundaries. By analyzing the captured image to identify actual mask region boundaries, the system can adapt the mask region definition to match the actual imaging conditions, maintaining processing accuracy even when imaging light reaches beyond predetermined boundaries.
Solution Approach 2:
The system changes the mask region parameters based on the captured image characteristics. By determining the mask type and adjusting mask region boundaries according to the captured image analysis, the system can adapt processing parameters to match actual imaging conditions, resolving the conflict between fixed boundary simplicity and dynamic boundary accuracy.
Data Source
AI summary
A medical image capturing system captures imaging light including a subject image obtained by irradiating a body cavity with illumination light from a light source unit, and includes: an imaging unit that captures, via a scope, a captured image including an imaging region where the imaging light reaches an imaging surface and a mask region where the imaging light does not reach the imaging surface; an exposure state determination unit that determines an exposure state on the basis of information of pixels within a predetermined range of the captured image; and a processing unit that executes processing by setting a type of the mask region as a first mask type determined on the basis of the captured image or a second mask type determined on the basis of an image acquired before the imaging according to the exposure state.