Generation of magnifying endoscopic images of gastric neoplasms based on an all-in-focus algorithm

BACKGROUND AND AIM

Magnifying endoscopy is useful for diagnosis of early gastrointestinal neoplasms by visualizing microvascular (MV) and microsurface (MS) structures of the mucosa when combined with image-enhanced endoscopy. However, precise control of the endoscope is needed because the depth of focus is narrow and the target may move. These problems may be overcome by the all-in-focus (AIF) technique, which was developed in the engineering field. The aim of the study was to evaluate magnifying endoscopic image with AIF algorithm.

METHODS

Twenty gastric neoplasms were examined. Images were acquired at 80× magnification and converted to endoscopic images with an AIF algorithm (EI-AIF). The focus area and MV and MS patterns in the original image and the EI-AIF were compared on a 5-point Likert scale, where 5 indicates that the EI-AIF was superior. Intraclass correlation coefficients (ICCs) were used to assess the inter-evaluator reliability. An image quality measurement value was calculated for each image as an indicator of the degree of focus.

RESULTS

The scores for focus area, MV, and MS were 4.78 ± 0.45 (ICC = 0.63), 4.12 ± 0.76 (ICC = 0.70), and 4.72 ± 0.52 (ICC = 0.45), respectively, with the EI-AIF significantly superior for all three items (P < 0.05 by Student's t-test). ICCs for the focus area and MV were > 0.60, indicating strong inter-evaluator reliability. Image quality measurement was higher for the EI-AIF compared with the original image in every case.

CONCLUSIONS

Endoscopic observation with AIF algorithm gives a better image quality that allows easier evaluation of MV and MS patterns. This technique may resolve the difficulties with magnifying endoscopic observation.