Imorgon vs. Fluency for Imaging

Significantly improve the speed and quality of Radiology reporting by reducing unnecessary dictation, particularly for ultrasound and DEXA. Imorgon transfers modality measurements into Powerscribe/Fluency/RadAI merge fields/tokens, eliminating manual entry errors. Imorgon's specialized services offer the following advantages: - All measurements are always transferred (usually DICOM SR) - Electronic worksheets capture findings and insert them into Powerscribe/Fluency/RadAI (rather than dictating from a worksheet) - Worksheets with priors, calculators, and clinical decision support (TI-RADS, O-RADS, etc) - Integrate into Epic or other EHRs - Vendor neutral - Support to ensure everything continues working Significant improvement in the overhead of reporting with a quick ROI.

Fluency for Imaging is an AI-powered radiology reporting platform developed by Jacobian to support faster, more accurate diagnostic reporting in medical imaging workflows. Radiology departments face increasing workloads and complex reporting requirements, which often lead to documentation inefficiencies and cognitive overload for clinicians. Fluency for Imaging addresses these challenges by combining advanced speech recognition technology, AI-driven automation, and structured reporting capabilities into a unified reporting environment. Radiologists can dictate reports using natural speech while the platform automatically organizes the narrative into structured clinical documentation. The system integrates directly with PACS platforms to transfer measurement data, imaging findings, and AI-generated insights directly into the report, eliminating manual transcription and reducing the potential for errors. Fluency for Imaging also incorporates large language model–based ambient reporting features that can listen to dictations, understand clinical context, and generate structured impressions automatically. Built-in guideline support and intelligent nudging help ensure reports follow established medical standards such as BI-RADS, PI-RADS, and TNM classifications. The platform also enables ontology-based coding using clinical standards including RadLex, SNOMED CT, and ICD-10, transforming unstructured text into structured, data-rich reports suitable for analytics, research, and clinical decision support. Multimedia reporting features allow radiologists to include annotated images, tables, and visual diagrams to improve report clarity for referring physicians. Additionally, Fluency for Imaging supports interoperability through standards such as HL7, FHIR, and FHIRcast, enabling seamless communication between imaging systems, hospital information systems, and analytics platforms.