An AI radiologist that reads MRI scans and drafts the preliminary report as a radiology resident, ready for board-certified radiologist review and sign-off.
The first available module is the PFI Engine, a fully automated knee MRI analysis producing 14 quantitative patellofemoral instability indices and structured clinical output.
Research preview. Not a medical device. Not for clinical diagnosis.
Poluneev develops AI radiology tools that automatically read imaging studies and produce structured preliminary reports - ready for radiologist sign-off. The workflow mirrors how an attending physician reviews a resident's preliminary read.
Our goal is to minimize the time radiologists spend on report assembly. The AI automatically detects all relevant pathologies, cross-validates findings internally, and produces a structured report ready for radiologist review and sign-off. The radiologist's attention stays where it matters - clinical interpretation.
Building the full musculoskeletal AI radiology stack.
Drop a DICOM study. Get a clinical-ready report in seconds.
From DICOM upload to clinical output in seconds. No manual landmarking, no slice picking, no measurement loop. The pipeline handles series identification, slice selection, landmark detection, and threshold application end-to-end.
14 quantitative indices across 4 clinical domains: patellar height (IS, CDI, PTI), trochlear morphology (3 cartilage + 4 bone indices), lateralization (PT-TG cart), and patellar tilt.
Every threshold from a peer-reviewed reference: Insall 1971, Caton 1982, Biedert 2006, Tanaka 2023, Pfirrmann 2000, Carrillon 2000, Sallay 1996, Hinckel 2017. No black-box scores.
Fully automated knee MRI analysis for patellofemoral instability.
The system computes 14 quantitative indices across four anatomical domains: patellar height, trochlear morphology, lateralization, and patellar tilt.
Try the PFI Engine with your own DICOM study. Your data is processed temporarily and never stored. You receive a structured clinical output ready for review.
Diagnostic radiologist building Poluneev - a comprehensive AI radiology system that automatically produces preliminary reports for radiologist sign-off. The first knee MRI module starts with the PFI Engine; the broader knee module is in active development, followed by the full musculoskeletal roadmap.
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Chicago, IL, USA