Evaluation of super resolution technology for digestive endoscopic images.

ABSTRACT:

Object

This study aims to evaluate the value of super resolution (SR) technology in augmenting the quality of digestive endoscopic images.

Methods

In the retrospective study, we employed two advanced SR models, i.e., SwimIR and ESRGAN. Two discrete datasets were utilized, with training conducted using the dataset of the First Affiliated Hospital of Soochow University (12,212 high-resolution images) and evaluation conducted using the HyperKvasir dataset (2,566 low-resolution images). Furthermore, an assessment of the impact of enhanced low-resolution images was conducted using a 5-point Likert scale from the perspectives of endoscopists. Finally, two endoscopic image classification tasks were employed to evaluate the effect of SR technology on computer vision (CV).

SUBMITTER: Lin J 

PROVIDER: S-EPMC11489312 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature