Healthcare
Earth Observation
Industry 5.0
Medical Image Management
General Anatomy
Imaging Standardisation
Standardising 10,500+ Studies for AI-Ready Medical Imaging
December 23, 2025
Enlitic
Enlitic develops AI-driven solutions that help healthcare organisations manage, structure, and operationalise medical imaging data at scale.
Inconsistent medical imaging data across modalities, vendors, and acquisition protocols increases clinical risk and limits the reliable use of imaging for AI analysis and downstream clinical applications.
Project Goals
- Standardise heterogeneous medical imaging across modalities, series, and vendors
- Improve interoperability and consistency at both study and series levels
- Deliver structured, AI-ready imaging data while preserving clinical integrity
Introduction
Enlitic develops AI-driven solutions that help healthcare organisations manage, structure, and operationalise medical imaging data at scale.
Main Challenge
Inconsistent medical imaging data across modalities, vendors, and acquisition protocols increases clinical risk and limits the reliable use of imaging for AI analysis and downstream clinical applications.
Goals
- Standardise heterogeneous medical imaging across modalities, series, and vendors
- Improve interoperability and consistency at both study and series levels
- Deliver structured, AI-ready imaging data while preserving clinical integrity
Enabling large-scale, AI-ready medical image standardisation
Through protocol-driven workflows and hybrid clinical expertise, Ingedata delivered consistent, high-quality imaging datasets suitable for AI and clinical use.
Project Impact
10,500+
MRI studies standardised at scale
Improved consistency and interoperability across imaging datasets
Reliable foundations for AI analysis and clinical decision support
Large-Scale Medical Image Harmonisation and Quality Assurance
Multi-Modal MRI Data Harmonisation
Reviewed and standardised MRI studies across multiple planes, kernels, acquisition settings, and vendors to ensure consistency at both study and series levels.
0
1
Multi-Modal MRI Data Harmonisation
Image Quality and Artefact Management
Identified and addressed artefacts, positioning issues, and motion-related quality degradation to preserve diagnostic usability.
0
2
Image Quality and Artefact Management
Clinical Series Classification
Differentiated diagnostic imaging series from procedural and guidance-related acquisitions to support accurate downstream analysis.
0
3
Clinical Series Classification
Protocol-Based Imaging Standardisation
Standardised laterality, windowing, reconstruction kernels, and contrast phases using protocol-driven rules to ensure consistency across datasets.
0
4
Protocol-Based Imaging Standardisation
Study- and Series-Level Quality Assurance
Applied structured QA processes at both study and series levels to ensure accurate labelling, consistency, and AI readiness.
0
5
Study- and Series-Level Quality Assurance
IngeData is a great, effective partner and I’m glad we decided to work with them. They helped us set up a scalable annotation process with a hybrid team of radiologists and technologists. What we previously handled in-house simply wasn’t scalable — IngeData made the process much easier.
Steven Rankin
Chief Strategy Officer
Enlitic
