Candidates in context
Move from a suggestion to its location in the CT study.
AI-ASSISTED LUNG CT ANALYSIS
A second set
of eyes.
A clearer view.
Pulmonary nodule intelligence, built around the radiologist. Bringing potential findings into focus, with a thoughtful AI-assisted review workflow.
Platform in developmentHuman expertise at the center
INTELLIGENCE, IN CONTEXT01 / LUNG CT
01AI candidate
Slice 142 / 284
AI-assisted. Expert-led.Designed to support your next look.
A thoughtful second-reader experience.
THE CLINICAL CONTEXT
Hundreds of slices. Every detail matters.
Chest CT brings extraordinary detail—and a demanding volume of information. Radiologists balance careful visual review with the pace and complexity of everyday practice.
We’re building an additional layer of attention, so expertise can stay focused on interpretation.
A complementary layer of attention.ADDITIONAL ATTENTIONA finding brought into focus
CONCEPTUAL IMAGE STACKA THOUGHTFUL SECOND READER
From a potential finding to an informed review.
Specialized AI, working together. Clinical judgment, always with you.
Candidate detection
POTENTIAL FINDINGS
01
Right lungCandidate region
02
Conceptual workflow previewLeft lungCandidate region
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 viewProposed workflow · Clinical validation plannedInside the workflow
COLLABORATIVE INTELLIGENCE
More than a single model.
One considered workflow.
Specialized AI agents, each with a clear role. A detection layer looks broadly. A verification layer considers the candidates. You bring the clinical perspective.
Our approach to intelligence- 01CT studyThe complete picture
- 02Detection agentFind candidates
- 03Verification agentAssess candidates
- 04Clinical reviewInspect in context
- 05RadiologistThe final decision
SPECIALIZED AGENTS. SHARED CONTEXT.The radiologist makes the final decision.
THE PLATFORM EXPERIENCE
See the finding. Keep the full picture.
Explore an illustrative review experience. Move between candidates, inspect their location and make your own assessment—directly in the study.
Try selecting a candidate below01AI candidate
Slice 142 / 284
Illustrative series navigation
Interface concept · Sample image and fictional annotationsExplore the platform
DESIGNED FOR RADIOLOGISTS
Your workflow. Your perspective.
A useful assistant should fit the way you think, see and review. That is where our design begins.
A focused review
A considered candidate list, designed to support attention.
You remain in control
Inspect, accept or dismiss. The interpretation is yours.
Reviewable AI assistance
Visible regions and clear review states, rather than a hidden verdict.
OUR GUIDING PRINCIPLE
Intelligence that supports
the person behind the image.
Medical imaging is more than pattern recognition. It is experience, context and clinical judgment. We’re building AI to extend that expertise, with every suggestion open to review and every decision kept human.
Human + AI. A clearer view, together.
EVIDENCE BEFORE ASSURANCE
Built with a research mindset.
Trust begins with a clear understanding of what a system can—and cannot—do. Our evaluation framework is being shaped around that responsibility.
- Patient-level dataset separation
- Detection and false-positive analysis
- Planned independent validation
EVIDENCE FRAMEWORKValidation planned
Sensitivity—
Pending validation
Precision—
Pending validation
False positives / scan—
Pending validation
Subgroup performance—
Pending validation
Performance results will be published following validation.
A FOCUSED START. A BROADER VISION.
Lung CT is the beginning.
We’re building a foundation for imaging intelligence, one carefully evaluated capability at a time.
Pulmonary nodule
detection
A focused starting point for AI-assisted chest CT review.
01 / FOUNDATIONIntelligent candidate
verification
A specialized layer to assess potential findings in context.
02 / REFINEMENTLongitudinal imaging
intelligence
Exploring comparison over time and future clinical decision support.
03 / HORIZONPlanned capabilities are subject to research, validation and applicable regulatory requirements.
FOR HOSPITALS & IMAGING CENTERS
Designed for the
bigger clinical picture.
Useful intelligence must also work in practice. We’re considering scalable analysis, deployment flexibility and future PACS/RIS interoperability from the beginning.
Explore clinical collaborationIntegration in mind
A design direction for future clinical interoperability.
Room to scale
An architecture intended to support growing study volumes.
Clinical review at the core
AI findings remain visible and open to clinician assessment.
THE COMPANY WE’RE BUILDING
The intelligence layer
for medical imaging.
Pulmonary nodule detection is our starting point. Our ambition is a broader platform that helps clinicians find meaningful information in increasingly complex imaging data.
Meet our missionMEET OUR TEAM
The minds behind IMedTwin.
Artificial intelligence, biomedical engineering and clinical radiology. Different perspectives, united by a clearer vision for medical imaging.
Nima Shafiei
Senior Computer Vision Engineer
Dr. Amir Abbas Amini
Senior Biomedical Engineer
Meysam Mansouri
Senior Biomedical Engineer
Dr. Leila Ostovar
Radiologist
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.