Mediaire provides AI‑driven software that automatically segments, quantifies, and detects pathologies in MRI scans, delivering standardized reports with norm‑value comparisons within minutes. The tools integrate directly into existing PACS/RIS workflows on local servers, ensuring data security while reducing radiologists' workload and improving diagnostic consistency across neuroradiology, prostate, and musculoskeletal imaging.
Funding
$12.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
4OLFFounders
Product
Problem
Radiologists must manually assess MRI scans, a process that is time‑consuming, subject to inter‑observer variability, and prone to missed subtle findings, especially in complex neuroradiology cases such as dementia, multiple sclerosis, aneurysms, and brain tumors.
Solution
Mediaire offers AI‑driven software modules (mdbrain, mdprostate, mdknee, etc.) that automatically segment anatomical structures, quantify volumes, and detect pathological lesions directly from DICOM MRI data. The tools run on local hardware, integrate with existing PACS/RIS systems, and generate standardized reports with norm‑value comparisons within 3–5 minutes of image acquisition. By providing objective, reproducible measurements and a second‑opinion overlay, the solution speeds up routine reporting, reduces workload, and improves diagnostic confidence for critical findings. The platform supports longitudinal analysis, enabling clinicians to track disease progression over time without additional manual effort.
Target Audience
Primary customers are hospital radiology departments and large imaging centers that perform routine neuroradiology, prostate, and musculoskeletal MRI examinations and require integrated AI assistance for faster, more reliable reporting.
Features
- Automatic segmentation and volumetric analysis of brain structures for dementia and multiple sclerosis assessments
- Lesion characterization and quantification with AI models for MS lesion load and new lesion detection
- High‑sensitivity aneurysm detection (>5 mm) and tumor differentiation (glioma, metastasis, meningioma) with 100 % sensitivity for saccular aneurysms
- Seamless PACS integration via auto‑pull, auto‑routing, and auto‑send of results; compatible with all major DICOM‑compatible MRI vendors (Siemens, Philips, GE, Canon/Toshiba)
- Local on‑premise deployment on modest Linux/Ubuntu servers (i7 CPU, 4 cores, 16 GB RAM, 500 GB HDD) ensuring patient data never leaves the facility
- Generation of concise, norm‑referenced reports with visual overlays, color‑coded maps, and longitudinal trend graphs
- Configurable automation workflows (Auto‑Pull, Auto‑Routing, Longi‑Pull, Auto‑Send) to eliminate repetitive manual steps