Amber Light-Assisted CBI Endoscopy for Superior Deep Vascular Visualization and Blood-Containing Tissue Depth Differentiation

• Published in: IEEE transactions on biomedical engineering Vol. 72; no. 8; pp. 2519 - 2531
• Main Authors: Zhang, Shipeng, Xie, Tianyu, Tuya, Gaowa, Ning, Guochen, Ma, Longfei, Zhao, Zhe, Fu, Ye, Liao, Hongen
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.08.2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Absorption; Algorithms; amber light; Animals; Biomedical engineering; Biomedical optical imaging; Blood; CBI endoscopy; Clinical trials; depth differentiation; Differentiation; Diseases; Endoscopes; Endoscopy; Endoscopy - methods; Equipment Design; Humans; image fusion; Image processing; Image Processing, Computer-Assisted - methods; In vivo methods and tests; Lighting; Medical imaging; Medical services; Mice; Optical imaging; Optical scattering; Performance evaluation; Precision medicine; Scattering; vascular structure; Visualization; Wavelengths; White light
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2025.3545853

Purpose : A novel compound band imaging (CBI) endoscopy system is introduced to enhance the visualization and depth differentiation of blood-containing tissues within mucosal structures. This system serves as a theranostics tool to supplement white light imaging (WLI), enabling more precise disease diagnosis and treatment. Methods : The system utilizes a combination of green and red narrow-band light, alongside amber wide-band light, synchronized with a rapid switching strategy and a color CMOS sensor. This design effectively avoids potential hardware cost increases associated with introducing additional narrow-band wavelengths and mitigates alignment challenges inherent in in vivo imaging using multiple narrow-band, time-separated techniques. Advanced image processing methods, including multi-scale HVS-guided contrast enhancement fusion and depth differentiation algorithms for blood-containing tissues, are employed to decouple images from the raw data and fuse spectral information. Results : The system underwent extensive testing to validate its imaging capabilities and methodology, yielding results that met expectations. Enhanced visibility and depth differentiation of vascular networks were demonstrated in both preclinical and clinical trials, with quantitative analyses confirming its superior performance compared to WLI. Conclusion : By integrating a sophisticated imaging setup with specialized processing algorithms, significant enhancements in imaging performance are achieved. Comprehensive evaluations confirm the system's feasibility, effectiveness, and potential for clinical translation. With further clinical validation, this system promises to advance endoscopic diagnostics and treatments by improving the clarity of critical vascular structures essential for clinical assessments.