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Gastric endoscopy is a standard clinical process that enables medicalpractitioners to diagnose various lesions inside a patient's stomach. If anylesion is found, it is very important to perceive the location of the lesionrelative to the global view of the stomach. Our previous research showed thatthis could be addressed by reconstructing the whole stomach shape fromchromoendoscopic images using a structure-from-motion (SfM) pipeline, in whichindigo carmine (IC) blue dye sprayed images were used to increase featurematches for SfM by enhancing stomach surface's textures. However, spraying theIC dye to the whole stomach requires additional time, labor, and cost, which isnot desirable for patients and practitioners. In this paper, we propose analternative way to achieve whole stomach 3D reconstruction without the need ofthe IC dye by generating virtual IC-sprayed (VIC) images based onimage-to-image style translation trained on unpaired real no-IC and IC-sprayedimages. We have specifically investigated the effect of input and output colorchannel selection for generating the VIC images and found that translatingno-IC green-channel images to IC-sprayed red-channel images gives the best SfMreconstruction result.

Stomach 3D Reconstruction Based on Virtual Chromoendoscopic Image Generation