Towards AI-augmented radiology education: a web-based application for perception training in chest X-ray nodule detection.

ABSTRACT:

Objectives

Artificial intelligence (AI)-based applications for augmenting radiological education are underexplored. Prior studies have demonstrated the effectiveness of simulation in radiological perception training. This study aimed to develop and make available a pure web-based application called Perception Trainer for perception training in lung nodule detection in chest X-rays.

Methods

Based on open-access data, we trained a deep-learning model for lung segmentation in chest X-rays. Subsequently, an algorithm for artificial lung nodule generation was implemented and combined with the segmentation model to allow on-the-fly procedural insertion of lung nodules in chest X-rays. This functionality was integrated into an existing zero-footprint web-based DICOM viewer,

SUBMITTER: Borgbjerg J 

PROVIDER: S-EPMC10646630 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature