Virtual Chromoendscopy with Tunable Visibility Enhancement

2026-07-14

AI Summary

This work proposes the first virtual chromoendoscopy method that supports user-defined enhancement levels, addressing the limitations of conventional dye-based chromoendoscopy, which increases cost and procedural time, thereby hindering diagnostic efficiency. By integrating a learnable image translation model with controllable image enhancement techniques, the approach establishes a unified framework capable of generating high-quality, multi-level virtual chromoendoscopic images directly from standard white-light endoscopic inputs. The method significantly improves the visualization of early gastric lesions, enabling flexible and personalized lesion representation without the need for exogenous dyes, thus balancing procedural efficiency with enhanced diagnostic support.

Abstract

Chromoendoscopy (CE) is a common clinical practice that sprays indigo carmine blue dye onto the gastric surface to improve the visibility of gastric lesions, such as an early cancer. While CE is effective in detecting the lesions, preparing and spraying the dye needs additional cost and time, which is undesirable both for patients and medical practitioners. To overcome this issue, virtual chromoendoscopy (V-CE) was recently proposed, which applies a learned image translation model to virtually generate a CE image from a standard endoscopy (SE) image. In this paper, we propose virtual enhanced chromoendoscopy (V-ECE) that combines V-CE with image enhancement techniques to further improve the visibility of gastric lesions. Because a desired enhancement level depends on the inspected lesion and the practitioner's preference, we introduce a novel image translation model that can generate V-ECE images using an enhancement level tunable by a user. Experimental results demonstrate that our proposed model can plausibly generate V-ECE images with various enhancement levels using a unified model.

Problem

• chromoendoscopy
• virtual chromoendoscopy
• gastric lesions
• image enhancement
• visibility enhancement

Innovation

• virtual chromoendoscopy
• tunable enhancement
• image translation
• gastric lesion visibility
• endoscopic imaging