Spectral Image Diagnostic System for Tissue Discrimination
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Solution Overview
Problem
Current diagnostic systems lack practical methods to visually identify and quantify diseased portions in living tissues by comparing spectral properties, making it difficult to discriminate between healthy and diseased areas during medical procedures.
Innovation Solution
A diagnostic system that uses spectral image pickup and processing to generate an indicator image by calculating an index-value (β or γ) based on specific wavelengths of light absorption properties, specifically focusing on the ratios of oxyhemoglobin and deoxyhemoglobin, allowing for precise discrimination between healthy and diseased tissues through color-coded images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If spectral image pickup means is used to obtain spectral image data, then spectral information can be obtained from living tissue, but it becomes difficult to visually identify and locate diseased portions without additional processing
Solution Approach 1:
The patent creates a visual copy of spectral information by generating an indicator image that represents spectral properties. The image processing means calculates index values from spectral image data and displays them as an indicator image on a monitor, allowing operators to visually locate diseased portions without directly analyzing complex spectral data.
Solution Approach 2:
The patent introduces an intermediary processing system between spectral image pickup and visual observation. The image processing means acts as a mediator that transforms spectral image data into an indicator image with calculated index values, making the spectral information visually interpretable for disease detection.
2Reliability
If spectral properties are used to discriminate between healthy and diseased portions, then disease detection becomes possible, but the diagnostic process becomes complex and time-consuming
Solution Approach 1:
The patent transforms complex spectral properties into simplified index values by changing the parameter representation. The image processing means calculates specific index values (β and γ) from spectral image data at different wavelengths, converting complex spectral analysis into quantitative metrics that can be rapidly processed and displayed.
Solution Approach 2:
The patent applies different processing to different regions of the tissue by calculating index values for each pixel in the spectral image. This allows localized discrimination between healthy and diseased portions, with each pixel's index value reflecting the spectral properties of that specific location, enabling precise spatial mapping of disease extent.
3Measurement precision
If multiple wavelength measurements are taken to calculate index values, then discrimination between healthy and diseased portions improves, but processing complexity increases
Solution Approach 1:
The patent segments the spectral analysis into discrete wavelength measurements. The image processing means separately measures spectral image data at multiple specific wavelengths (e.g., 542 nm, 558 nm, 578 nm) and then combines these segmented measurements to calculate index values, simplifying the processing of multi-wavelength data.
Solution Approach 2:
The patent uses a selective approach by measuring spectral properties at specific key wavelengths rather than analyzing the entire spectral range. This partial measurement strategy focuses on wavelengths most relevant for discriminating between healthy and diseased tissue, reducing processing complexity while maintaining discrimination precision.
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 rapid and precise identification of diseased areas, reducing diagnosis time and facilitating surgical excisions by providing a visual indicator of tissue health, thereby improving surgical accuracy.
Implementation Method 1
obtain the spectral property (the distribution of light absorption property for each frequency) of a living tissue
Implementation Method 2
the spectral property of a substance reflects information concerning the types or densities of components contained in the vicinity of a surface layer of a living tissue
Data Source
AI summary
A diagnostic system comprises a spectral image pickup means that picks up a spectral image in a predetermined wavelength region in a body cavity and obtains spectral image data, an image processing means that obtains, from the spectral image data, an index-value for discriminating between a diseased portion and a healthy portion, and generates and outputs an indicator image based on the index-value, and a monitor on which the indicator image is displayed, wherein, for each pixel of the spectral image, the image processing means defines β obtained by a predetermined expression as the index-value, while using the spectral image data P1 at a first wavelength which is around a wavelength of 542 nm, the spectral image data P2 at a second wavelength which is around a wavelength of 558 nm and the spectral image data P3 at a third wavelength which is around a wavelength of 578 nm.