Radiology Practices

Your images leave.
The patient stays.

Annalise.ai and Aidoc keep coming up in strategy meetings. Legal keeps saying no because the images have to leave the network with patient identifiers still attached. PixelIQ removes that blocker - inline, on-prem, before any study reaches any AI vendor.

113+
DICOM attributes
<50ms
Per study
PS3.15
Compliant
PixelIQ · live anonymisation stream
(0008,0050)AccessionNumber██████████████stripped
(0010,0010)PatientName██████████stripped
(0010,0020)PatientID█████████stripped
(0010,0030)PatientBirthDate19620000pseudonymised
(0008,0020)StudyDate20240814retained
(0008,0060)ModalityCTretained
(0008,103E)SeriesDescriptionCHEST W CONTRASTretained
(0010,21B0)AdditionalHistory██████████████████stripped
8 of 113 attributes shown · PS3.15 E.1 profile47ms
What changes

Before and after PixelIQ.

Everything currently standing between your practice and an Annalise.ai or Aidoc partnership.

Without SECUVA
Annalise.ai requires direct DICOM upload to their cloud - patient names in every header
With PixelIQ
PixelIQ anonymises inline. Annalise.ai gets clean studies. Raw data never leaves your network.
Without SECUVA
Legal review takes 6–8 weeks before any AI vendor contract can proceed
With PixelIQ
PHI-free data path removes the core legal objection. Review compresses to days.
Without SECUVA
PACS export misses burnt-in pixel text on CT scouts and DX overlays
With PixelIQ
Pixel-level detection removes every PHI surface - headers, pixels, private tags
Without SECUVA
No record of which studies were shared with which vendor or researcher
With PixelIQ
Cryptographic audit log of every study movement, exportable for HREC review
Without SECUVA
Each new AI vendor requires a separate legal review from scratch
With PixelIQ
Policy engine governs multiple vendors simultaneously per their data-use agreements
The gap nobody talks about

Manual de-identification is not a DICOM strategy.
It is a liability waiting to surface.

Most radiology practices rely on PACS export settings and hope. Burnt-in pixel text in CT scouts, private creator tags, and secondary capture objects are invisible to header-only tools - and invisible to the practice until a breach notification arrives.

Typical PACS export coverage
DICOM PS3.15 headerscovered
Burnt-in pixel PHImissed
Private creator tagsmissed
SR / KO documentsmissed
Secondary capture SOPsmissed
How it works

The PixelIQ pipeline.

Runs inside your network. Nothing raw ever leaves.

01
PACS / Modality
Study arrives via DICOM C-STORE or WADO
02
Pixel Analysis
Pixel-level detection across all SOP classes
03
Header Scrub
All 113+ PS3.15 attributes processed per configured profile
04
Policy Check
Routing rules validated, recipient allowlist enforced
05
Governed Output
Clean study delivered. Cryptographic audit entry written.
Day one

Three things that change immediately.

PixelIQ deployed as DICOM proxy

Our team installs the agent between your PACS and the first downstream destination. Radiologists notice nothing. IT does not reconfigure modalities. Typically 4–8 hours on-site.

No workflow changes for clinical staff

Annalise.ai or Aidoc connected

Your existing AI vendor relationship connects to the governed pipeline. They receive exactly what the data-use agreement permits. The legal blocker is architecturally removed.

Multiple vendors, single policy engine

First audit log ready

Every study that moves generates a cryptographic audit entry - timestamped, signed, exportable. From day one you have a compliant record of every data movement, ready for any review.

Exportable for HREC or TGA audit
Capabilities

What PixelIQ covers.

Pixel-level PHI detection

A pixel-level detection model trained on radiology imaging - patient banners, accession overlays, clinic watermarks - identifies and removes PHI invisible to any header-only tool. Covers CT, MR, DX, MG, CR, XA, NM, and all secondary capture objects.

SOP classes
CT ImageMR ImageDX ImageMG ImageSC ImageSR DocumentXA ImageNM Image

PS3.15 header scrub

All E.1 and E.2 profile attributes processed, configurable retain/remove/pseudonymise per tag.

SR & KO handling

Structured Reports, Key Objects, and Presentation States processed natively - not skipped.

Policy-gated routing

Each destination receives only what its data-use agreement permits. Enforced at network layer.

Immutable audit chain

Every anonymisation decision cryptographically signed. Tamper-evident log for HREC and TGA.

Technical specifications

Built for PACS integration, not alongside it.

PixelIQ runs as a transparent DICOM proxy. Your PACS does not know it is there. No workflow changes for radiologists. No integration project for IT.

Protocol support
DICOM C-STORE, WADO-RS, WADO-URI, DICOMweb
DICOM profile
PS3.15 E.1 Basic Application Confidentiality · E.2 Retain Safe Private Option
Pixel PHI detection
Pixel-level detection - DX, CT, MR, MG, CR, SC, XA, NM
Throughput
<50ms per study
Deployment
On-prem agent · no cloud data path for raw studies
Audit format
Cryptographically-signed audit format · exportable for HREC / TGA review
Retention policy
Configurable per-recipient · expiry enforcement at routing layer
Compliance
DICOM PS3.15, OAIC APP 11, TGA SaMD pathway, ISO 27001
Questions

What radiology teams usually ask us.

01

Annalise.ai keeps coming up in our AI strategy meetings. Why can't we just share studies directly with them?

You can - with PixelIQ in place. Annalise.ai, Aidoc, and similar vendors receive a governed, PS3.15-compliant dataset. The raw studies with patient identifiers never leave your network. You retain the audit trail. The contract review cycle shortens dramatically because the data-sharing risk is architecturally removed.

02

Our PACS already has de-identification settings. Isn't that enough?

For most deployments, no. PACS de-identification tools process header fields reliably, but they systematically miss burnt-in pixel text on scout images and overlays, private creator tags from vendors like Siemens and GE, and secondary capture objects (SC SOPs). These surfaces carry patient identifiers that don't appear in standard DICOM headers - and are invisible to the practice until a breach notification arrives.

03

What about burnt-in pixel text on CT scouts and DX images?

That is the surface PixelIQ was specifically built for. A pixel-level detection model trained on radiology imaging - patient banners, accession number overlays, clinic watermarks - detects and removes pixel-level PHI across every SOP class. Header-only tools cannot do this.

04

How does PixelIQ interact with our existing PACS and radiology workflow?

PixelIQ operates as a transparent DICOM proxy. Your PACS sends studies the same way it always has. Radiologists see no change. IT does not need to reconfigure modalities. PixelIQ sits inline and processes studies before they reach any downstream destination - on-prem, sub-50ms per study.

05

What is our liability position under the Australian Privacy Act if something goes wrong?

Under APP 11, you are required to take reasonable steps to protect the personal information you hold. Sending identifiable DICOM to an AI vendor without architectural controls is difficult to defend as 'reasonable'. With PixelIQ, PHI never reaches the external recipient - which is the only framing that clearly satisfies the obligation.

06

How long does a trial deployment take?

A typical sandbox deployment - where we connect PixelIQ to your PACS, configure the anonymisation profile, and run a live demo against your study formats - takes 4–8 hours on-site. There is no disruption to production workflows during the trial.

Get started

See PixelIQ on your DICOM infrastructure.

We will connect to your PACS in a sandbox and run a live anonymisation demo against your study format.

No data leaves your site during the demo. 4–8 hours on-site.