Evaluation of an improved computer-aided detection system for Barrett's neoplasia in real-world imaging conditions.

ABSTRACT:

Background

 Computer-aided detection (CADe) systems may improve detection of Barrett's neoplasia. Most CADe systems are developed with data from expert centers, unrepresentative of heterogeneous imaging conditions in community hospitals, and therefore may underperform in routine practice. We aimed to develop a robust CADe system (CADe 2.0) and compare its performance to a previously published system (CADe 1.0) under heterogeneous imaging conditions representative of real-world clinical practice.

Method

 CADe 2.0 was improved through a larger and more diverse training dataset, optimized pretraining, data augmentation, ground truth use, and architectural adjustments. CADe systems were evaluated using three prospective test sets. Test set 1 comprised 428 Barrett's videos (114 p

SUBMITTER: Jong MR 

PROVIDER: S-EPMC12659990 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature