Contrast-Enhancing Snapshot Narrow-Band Imaging Method for Real-Time Computer-Aided Cervical Cancer Screening

Composition of cervical precancerous lesions and carcinoma in situ is rich in hemoglobin, unlike healthy tissues. In this study, we aimed to utilize this difference to enhance the contrast between healthy and diseased tissues via snapshot narrow-band imaging (SNBI). Four narrow-band images centered at wavelengths of characteristic absorption/reflection peaks of hemoglobin were captured with zero-time delay in between by a custom-designed SNBI video camera. Then these spectral images were fused in real time into a single combined image to enhance the contrast between normal and abnormal tissues. Finally, a Euclidean distance algorithm was employed to classify the tissue into clinical meaningful tissue types. Two pre-clinical experiments were conducted to validate the proposed method. Experimental results indicate that contrast between different grades of diseased tissues in the SNBI generated image was indeed enhanced, as compared to conventional white light image (WLI). The computer-aided classification accuracy was 100% and 50% as compared to the gold standard histopathological diagnosis results with the SNBI and the conventional WLI methods, respectively. Further, the boundary contour between health tissue, cervical precancerous regions, and carcinoma in situ can be automatically delineated in SNBI. The proposed SNBI method was also fast, and it generated automatic diagnostic results with clear boundary contours at over 11 fps on a Pentium 1.6-GHz laptop. Hence, the proposed SNBI is of great significance to enlarge worldwide the coverage of regular cervical screening program, and to live guide surgeries such as biopsy sample collection and accurate cervical cancer treatment.