What's New

In the RadioView.AI AI Marketplace the unit of the decision is now the site. Pick a site and the catalogue answers for that site, start a trial or request a subscription against it specifically, and read indication of use and regulatory status as columns of the catalogue. A subscription request lands as a pending approval rather than switching the model on.

MonitorAI holds AI results against the radiologist's completed report, so you can see how each model performs on your own studies. A review worklist for cases where AI and report disagree, case-level adjudication, per-site scoping, model cards, and exports for your QA meeting.

AI Analysis runs three cleared AI Suite modules against a study as it arrives and surfaces what they flagged in the viewer, with a confidence score where the model reports one. Each module triages and prioritizes within its own cleared indication. One click drops a flagged result into your draft report.

Send a study, or fifty, from RadioView.AI to an external PACS over standards-based DICOM. Destinations are saved once and verified with a C-ECHO before anything moves, batch transfers run in the background, and every send is logged per destination.

AI Hanging Protocols automatically arrange radiology images by modality, body part, clinical context, and each radiologist's reading preference — learning from DICOM metadata and adapting as the data changes, so the study is laid out before you open it.

RadioView.AI has received FDA 510(k) clearance (K260936) as a Class II Medical Image Management and Processing System. This is a clearance for the imaging layer itself, not for an individual AI module: the web-based PACS that viewing, transmission, storage and visualization run on.

VesselViz brings 3D vessel visualization to CT Angiography in the AI Viewer — with automated centerline extraction, curved planar reformation (CPR), and per-vessel diameter measurements, so you can assess a vessel without leaving RadioView.AI.

The full RadioView.AI web app now adapts to phones and tablets — worklist, dashboard, reporting, and Comhub — with a mobile navigation shell, so you can pick up work from any screen in your browser, no separate download required.

Open a study and RadMatcher loads the matching report template automatically, so you can start dictating right away. It matches to your personal templates when available and feeds straight into report generation.

The RadioView.AI viewer now runs on the latest Cornerstone3D v4 rendering engine (OHIF 3.12.5). Studies render faster and scroll more smoothly, and the viewer gains a modern labelmap segmentation toolset that the rest of this release builds on.

Large studies now stream in layers with HTJ2K encoding — a quick low-resolution preview appears first and sharpens to full diagnostic resolution as the rest arrives, so you start reading sooner instead of waiting for the whole file to download.

Comhub now adds real-time audio and video calls, huddles, and scheduled meetings to the team chat already built into RadioView.AI — so you can talk through a study with a colleague or care partner without leaving the workspace.

Drop a few prompt points on a structure and RadioView.AI outlines it for you, then interpolates the outline across slices — so you no longer have to segment every slice by hand. It uses a Segment Anything (SAM) model that runs in the browser.

The RadioView.AI viewer now has a dedicated annotation workflow. Drop arrows and free-text notes directly on any image, save them separately from your measurements, and have them reliably restored the next time you open the study — even after a refresh. No more lost markup, no more 'where did my arrow go?'

We've rebuilt the way you read studies in RadioView.AI. The new Reading Workflow Panel is a single, focused command center on the reading side — pick a hanging-protocol profile, jump through your worklist, navigate series and viewports, and jot down per-study notes, all without leaving the viewer.

RadioView.AI's latest update brings built-in team chat (Comhub), a radiologist-focused home dashboard, Key Images capture in the AI Viewer, anatomical measurements, and faster study streaming via ConnectAI local node.

AI-assisted measurement tools in RadioView.AI can reduce time spent on radiological assessments by up to 75%, while increasing accuracy by eliminating human error.

RadioView.AI now supports multi-monitor workspaces, eliminating window toggling and cramped views to boost productivity, reduce errors, and speed up reads.