[Quantization Methodology of Autofluorescence Bronchoscopy Image 
in the YUV System]

Area of Science:

• Pulmonology
• Medical Imaging
• Oncology

Context:

• Lung cancer diagnosis relies on accurate identification of bronchial abnormalities.
• Autofluorescence bronchoscopy (AFB) offers a visual method for detecting lesions.
• Quantitative analysis of AFB images can enhance diagnostic precision.

Purpose:

• To establish optimal reference values for YUV quantitative analysis of AFB images.
• To evaluate the efficacy of YUV values in differentiating various lung pathologies.
• To determine the significance of AFB in diagnosing central-type lung cancer.

Summary:

• Quantitative analysis of autofluorescence bronchoscopy (AFB) images using YUV color spaces was performed on biopsy-confirmed cases.
• Statistically significant differences in Y, U, and V values were observed between invasive cancer and other groups (normal mucosa, inflammation, LGD, HGD).
• YUV values effectively differentiated benign and malignant lung diseases, supporting AFB's role in lung cancer diagnosis.

Impact:

• Provides objective, quantitative data for interpreting AFB images.
• Enhances the accuracy of lung cancer diagnosis, particularly for central-type tumors.
• Establishes a foundation for standardized diagnostic criteria using AFB technology.