THE PLATFORM

A second reader.
Built into the picture.

An AI-assisted lung CT review platform in development. Designed to bring potential pulmonary nodules into focus, while keeping the radiologist at the center.

HUMAN EXPERTISE. INTELLIGENT ASSISTANCE.LUNG CT / 01
Lung CT / Review workspace
Analysis preview
STUDY
Chest CTAxial series
DEMO
Illustrative axial chest CT showing both lungs; displayed annotations are fictional
01AI candidate
ARLP
DEMO-001 · FICTIONAL STUDYWL −600 / WW 1500
50 mm
Slice 142 / 284
Illustrative series navigation
Interactive interface concept · Fictional AI output and demo study informationSelect a candidate to explore

FROM STUDY TO ASSESSMENT

A considered path through the study.

Three complementary stages. One connected review experience.

Illustrative chest CT input for the proposed AI workflow
Candidate detection
POTENTIAL FINDINGS
01
Right lungCandidate region
02
Left lungCandidate region
Conceptual workflow preview

A broad first look

A detection agent is being developed to examine chest CT images and identify potential pulmonary nodule candidates.

Potential findings brought into view

THE PROPOSED END-TO-END WORKFLOW

Clarity at every step.

From CT ingestion to clinician feedback, we’re designing each stage to serve the review.

01

Bring in the study

The intended workflow begins with a chest CT study. Ingestion and clinical connectivity are under development.

02

Analyze the images

A detection agent is being developed to surface potential pulmonary nodule candidates across the study.

03

Consider each candidate

The planned verification layer assesses candidate regions to help distinguish useful suggestions from unnecessary findings.

04

Review in context

The interface is designed to connect every candidate to its location, with the original study available for assessment.

05

Keep the decision human

Accept or dismiss suggestions. Clinical interpretation and responsibility remain with the radiologist.

06

Learn from the workflow

Structured review feedback is a planned input to product improvement, with data governance to be agreed before evaluation.

THE DESIGN PRINCIPLES

Useful assistance, in view.

01

Reviewable findings

Candidate regions and clear review states make the AI contribution visible.

02

A focused workspace

Study context, image navigation and candidate review in a connected interface.

03

Clinician-led decisions

A suggestion is an invitation to review. It does not establish a diagnosis.

04

Integration as a direction

Future interoperability and deployment options will be evaluated with clinical partners.

The interface illustrates our product direction. Features, integrations and clinical performance are subject to development and validation.

LET’S BUILD THE NEXT CHAPTER

A conversation today.
A clearer view tomorrow.

We’re looking to collaborate with radiologists, imaging centers
and clinical research partners.