Automatic bolus tracking in abdominal CT scans with convolutional neural networks.

ABSTRACT:

Background

Bolus tracking can optimize the time delay between contrast injection and diagnostic scan initiation in contrast-enhanced computed tomography (CT), yet the procedure is time-consuming and subject to inter- and intra-operator variances which affect the enhancement levels in diagnostic scans. The objective of the current study is to use artificial intelligence algorithms to fully automate the bolus tracking procedure in contrast-enhanced abdominal CT exams for improved standardization and diagnostic accuracy while providing a simplified imaging workflow.

Methods

This retrospective study used abdominal CT exams collected under a dedicated Institutional Review Board (IRB). Input data consisted of CT topograms and images with high heterogeneity in terms of anatomy, sex

SUBMITTER: Li AT 

PROVIDER: S-EPMC10167470 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature