Endoscope Image Conversion to Narrow-Band Imaging With Aberration Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current endoscopic imaging techniques face challenges in accurately identifying early-stage lesions due to deficiencies in chromatic aberration and brightness identification, leading to delayed diagnoses.
Innovation Solution
A method for converting endoscope images to narrow band images involves acquiring reference and narrow-band image data, generating hyperspectral and narrow-band simulated images, and adjusting light-source parameters using chromatic aberration data to enhance image clarity and identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional endoscopy is used for detection, then the device is simple and easy to operate, but early-stage lesions cannot be accurately identified due to insufficient image identification capability
Solution Approach 1:
The patent creates a virtual narrow-band image from standard endoscope images through computational processing. Instead of requiring physical narrow-band imaging equipment, the system generates a digital copy that simulates narrow-band imaging effects, thereby improving lesion detection capability while avoiding the complexity of specialized hardware
Solution Approach 2:
The patent transforms standard RGB images into narrow-band images by adjusting color space parameters and applying spectral transformation algorithms. This parameter-based conversion allows the system to enhance image identification capability for early lesions by modifying image processing parameters rather than changing the physical imaging device
2Measurement precision
If narrow band imaging is used to enhance image identification, then lesion detection capability is improved, but chromatic aberration and brightness identification deficiencies persist
Solution Approach 1:
The patent incorporates feedback mechanisms where the generated narrow-band images are compared against reference images, and the processing parameters are iteratively adjusted to minimize chromatic aberration and brightness errors. This feedback loop continuously optimizes the transformation to improve reliability of color and brightness representation
Solution Approach 2:
The patent performs preliminary calibration and correction of chromatic aberration during the image transformation process. By pre-adjusting color balance and spectral characteristics before final image generation, the system prevents chromatic and brightness errors rather than attempting to correct them afterward, thereby improving reliability
Data Source
AI summary
The present application discloses a method for converting endoscope images to narrow band images. Firstly, obtaining a reference image data and a narrow band reference image data of a reference object, for obtaining a hyperspectral reference image data, a narrow band conversion parameter and a first light source parameter by operation and then correspondingly obtaining a simulated narrow band image data, which is further compared with the narrow band reference image data to obtain a chromatic aberration data. A second light source parameter is obtained according to the first light source parameter and the chromatic aberration data. An input image data of an endoscope is converted to a narrow band input image data according to the narrow band conversion parameter and the second light source parameter. Thus, the image identification ability and the definition of the input image are improved.