The global radiologist shortage, rising scan volumes, and tightening EU data sovereignty requirements have made AI medical imaging a strategic necessity — not a future experiment. This guide compares the leading platforms in 2026 so you can choose the right solution for your department and patient population.
The most critical requirement for European healthcare organisations evaluating AI medical imaging is not just diagnostic performance — it is where patient data is processed. DICOM imaging studies represent some of the most sensitive personal data categories under GDPR. MAIA Brain's Medical Imaging AI processes all studies — CT, MRI, X-ray, PET — entirely on-premise within your hospital infrastructure. No patient data transits external servers. Combined with AI-powered triage that prioritises critical findings in real time, automated structured reporting across all major modalities, and full EU AI Act compliance including clinical decision explainability — MAIA Brain delivers measurable improvements in diagnostic safety and radiologist efficiency, without compromising data sovereignty.
Side-by-side comparison across the criteria that matter most to radiology departments, healthcare IT teams, and clinical procurement in 2026.
| Capability | MAIA Brain Medical Imaging AI | Aidoc | Zebra Medical Vision | Philips IntelliSite | Enlitic |
|---|---|---|---|---|---|
| Full On-Premise Deployment | Standard | Cloud Only | Cloud Only | Hybrid | Hybrid |
| Multi-Modality Support (CT / MRI / X-Ray / PET) | All Modalities | CT & X-Ray Focus | CT & Mammography | Multi-Modality | CT Focus |
| AI-Powered Critical Finding Triage | Real-Time, All Modalities | CT & CXR | CT Focus | Workflow Integration | Partial |
| Automated Structured Reporting | Native SR Generation | Alert-Based | Partial | Reporting Module | In Development |
| GDPR / EU Data Sovereignty | On-Premise — Full Control | US Cloud, Israeli HQ | US Cloud, Israeli HQ | EU Regions, Dutch HQ | Partial |
| EU AI Act Compliance (Clinical Explainability) | Built-In Explainability | Alert Overlays | Heatmaps | Partial | Limited |
| Native PACS / RIS Integration (DICOM / HL7) | Native, No Worklist Change | Yes | Yes | Deep Integration | Partial |
| Continuous Learning from Local Data | On-Premise Fine-Tuning | Centralised Cloud Model | Centralised Cloud Model | Partial | Federated Learning |
| Deployment Timeline | 4–6 Weeks, MAIA-Managed | 6–10 Weeks | 6–12 Weeks | 3–6 Months | 8–14 Weeks |
| Transparent Pricing | Flat Annual Fee | Per-Study Pricing | Per-Study / Custom | Enterprise Quote | Custom Quote |
Per-study pricing models from cloud-based platforms compound rapidly at scale. A busy radiology department performing 80,000 studies per year faces dramatically different cost trajectories depending on platform pricing structure — before GDPR compliance costs are factored in.
Cost comparisons are illustrative and based on publicly available per-study pricing models and typical deployment profiles. Actual costs vary significantly by institution size, contract terms, and modality mix. Request a MAIA Brain cost comparison tailored to your imaging volumes and environment.
Purpose-built for European healthcare environments — combining AI diagnostic accuracy with full on-premise patient data control, PACS-native integration, and EU AI Act clinical explainability from day one.
MAIA Brain analyses every study within minutes of acquisition and automatically scores critical findings — pulmonary emboli, intracranial haemorrhage, pneumothorax, spinal fractures, acute aortic pathology. Studies with urgent findings are automatically elevated to the top of the radiologist's worklist, regardless of arrival order. Time-to-treatment for life-threatening conditions reduces dramatically without requiring radiologist rule changes or worklist manual intervention.
MAIA Brain pre-populates structured radiology reports with AI-generated measurements, findings, and observations for routine studies — CT chest, abdominal CT, chest X-ray, brain MRI, and musculoskeletal imaging. Radiologists review, amend, and sign off rather than dictating from scratch. Reporting time per study reduces by 30–50% for standard studies, freeing radiologist capacity for complex cases and reducing transcription error rates.
A single MAIA Brain deployment covers all major imaging modalities and body regions: CT (chest, abdomen, pelvis, neuro, cardiac, musculoskeletal), MRI (brain, spine, abdomen, cardiac, MSK), plain film X-ray (chest, abdominal, MSK), PET-CT, and ultrasound image series. Departments do not need to procure and integrate separate point-solution AI tools for each modality — reducing integration complexity, licensing overhead, and staff training burden substantially.
All AI inference runs within your hospital's infrastructure. DICOM studies never leave your PACS environment — no de-identification pipeline, no cloud transfer, no data processing agreement with a third-country vendor. This eliminates the legal and technical complexity that cloud AI platforms create for EU healthcare providers operating under GDPR and national health data protection legislation. Data subject rights (access, erasure) remain entirely within your institution's control. Explore MAIA's AI Cyber Security Agent for complete organisational data protection.
Every AI finding is accompanied by explainability outputs that meet EU AI Act high-risk AI requirements: heatmap overlays showing which image regions influenced the finding, confidence scores, and the AI's structured reasoning. Radiologists understand exactly what the AI identified and why — enabling meaningful clinical review rather than black-box alert acceptance. All AI outputs are structured as clinical decision support requiring radiologist confirmation, satisfying human oversight obligations under both the EU AI Act and Medical Device Regulation.
MAIA Brain connects to any PACS or RIS using standard DICOM and HL7 protocols — no proprietary connectors, no worklist modifications, no disruption to existing radiologist workflows. AI results return as DICOM structured reports and SR annotations that appear directly in the PACS viewer alongside original images. The MAIA team manages full technical integration and clinical validation in 4 to 6 weeks. See also MAIA's broader intelligent automation platform for hospital-wide AI deployment beyond radiology.
MAIA Brain's structured healthcare deployment process eliminates the integration risk and lengthy validation periods that delay value realisation from traditional enterprise imaging AI deployments.
The MAIA team connects MAIA Brain to your existing PACS and RIS using standard DICOM and HL7 interfaces. No worklist modifications or radiologist workflow changes are required. All AI results return directly into your existing PACS viewer as structured annotations and reports.
MAIA Brain is validated against your department's historical imaging data — calibrating performance to your patient population, scanner hardware, and local protocols. Validation is completed on-premise; no patient data is transmitted externally. The validation report satisfies EU AI Act documentation requirements for high-risk AI clinical tools.
Once live, MAIA Brain operates continuously — triaging studies, generating structured report pre-populations, and surfacing AI findings alongside radiologist reads. The model learns continuously from your department's confirmed diagnoses (on-premise), improving accuracy for your specific patient population over time without any cloud data sharing.
MAIA Brain is purpose-built for a specific type of healthcare organisation. Here is an honest assessment of where it fits — and where alternatives may be more appropriate.
Before AI triage, our overnight on-call radiologist was reading studies in chronological order. A critical PE could sit in the queue for three hours behind routine knee MRIs. Within the first month of deployment, we had two cases where the AI triage flagged life-threatening findings that were elevated to the top of the queue immediately — both patients received treatment within the target door-to-treatment time. The data never left our servers, which was a non-negotiable requirement for our DPO.
Deployed in Healthcare Environments Across
Practical answers to the questions radiology departments, healthcare IT teams, and clinical procurement ask most frequently. More answers available on our full FAQ page.
Book a private clinical demonstration of MAIA Brain Medical Imaging AI — we will show you the AI in action on imaging modalities relevant to your department, and walk through exactly what integration in your PACS environment looks like.