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RadSR

SR/OCR

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.

RadSRCondensing

OCR'd US imagesmeasurements burned into the image~4,280tokens in

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BPD8.4 cmkeep

HC29.1 cmkeep

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AC26.7 cmkeep

FL6.2 cmkeep

EFW1,240 gkeep

check_circleCondensed SR — measurements only~180−96%

What it does

RadSR turns scanned or image-based documents into DICOM Structured Reports via OCR, and condenses SR payloads so downstream AI — your pipeline or RadFuzion’s built-in processing — gets clean, structured input. Extracted results are delivered via webhook with per-item delivery status.

Capabilities

check_circleCreate SR from OCR of scanned / image-based documents
check_circleCondense SR data for downstream AI pipelines
check_circleOptional built-in RadFuzion processing
check_circleDICOM SR parsing for standard templates
check_circleWebhook delivery with per-item status and payload inspection

convert_to_textRadSR field guideFrom DICOM SR to Clean Clinical Measurements: How RadSR Normalizes Structured ReportingSee how RadSR condenses native DICOM Structured Reports, extracts measurements from ultrasound and bone density images, protects PHI, and maps clinical meaning into stable reporting fields.Read the articlearrow_forward

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See RadSR in your workflow

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