Modules
Extend RadFuzion with purpose-built modules
Every module slots into the same platform. Turn on exactly what your workflow needs.
RadMatch
Study-description matching for teleradiology & priors
A fast ML engine that maps free-text study descriptions to your exam codes — a lifesaver for teleradiology groups and for normalizing priors brought in from outside facilities. LLM fallback for hard cases, review queue for anything low-confidence.
RadFetch
Automated prior-study prefetch
HL7 ORM-driven prefetch that automatically pulls relevant prior studies from your source PACS before the exam is read — with AI-assisted prior selection.
RadHub
Multi-node hub & spoke control center
A single control center for hub-and-spoke deployments: monitor every connected RadFuzion node, push configuration and routing rules out, and audit activity across the whole network.
RadSR
SR from OCR, and SR condensed for AI
Create DICOM Structured Reports from OCR’d images, and condense existing SR data for downstream AI or built-in RadFuzion processing.
RadRead
Downtime prelim PACS — dictation & fax
A resilience-first reporting fallback: when your cloud PACS or RIS is unavailable, radiologists keep reading and delivering preliminary reports — with speech transcription and AI-assisted impressions built in.
RadList
Modality worklist for cloud vendors without one
Serve a DICOM Modality Worklist (MWL) so modalities pull accurate order details straight from RadFuzion — filling the gap when your cloud PACS/RIS vendor doesn’t provide one.
RadShare
Secure node-to-node study sharing
Exchange exams securely between RadFuzion nodes over HTTPS, using system trust or pinned certificates — with full inbound/outbound tracking.
RadGen7
Generate DICOM from HL7 ORM
Create synthetic placeholder DICOM studies from HL7 ORM messages — useful for testing routing, seeding worklists, and standing in for pending images.
RadDicom7
Generate HL7 ORM from DICOM
Turn completed DICOM exams into HL7 ORM^O01 messages for downstream modality and information systems — one at a time or in batch.
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