top of page
Feature highlight

Automated quality control powered by artificial intelligence

Clinical trial pain-point

Manual quality control through visual inspection by a trained imaging professional is an expensive but crucial part of any imaging-based clinical trial. Data that does not comply with study specifications has the potential to delay or even derail your entire clinical trial.

SliceVault solution

To improve the manual quality control procedure, SliceVault uses artificial intelligences (AI) and an intelligent rule system to ensure all submitted studies comply with study specifications.


Automatic quality control checks

SliceVault assists the manual quality control procedure by analyzing studies for common imaging errors and submission mistakes. Results are easily accessible to the trained quality control professional in the embedded QC module.

Automatic quality control checks include:

  • contrast/no contrast

  • oral contrast

  • IV contrast in early phase

  • IV contrast in late phase

  • head/chest/abdomen/pelvis included in field of view

  • follow-up studies belongs to same subject as screening visit

  • data duplication (studies uploaded previously)

  • correct modality

  • correct slice thickness

  • missing slices


AI-Based Image Quality Assessment in CT. Edenbrandt L et al., Arch Clin Biomed Res 2022 DOI:10.26502/acbr.50170300

bottom of page