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Artificial Intelligence Operating System for Medical Imaging

Enhance physician workflow with state-of-the-art AI models, for research, seamlessly integrated with your existing PACS.

Features

Why use PACS AI Logo ?

Enhance your diagnostic capabilities with our comprehensive AI-powered platform.

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Seamless PACS Integration

Use AI without infrastructure overhaul.

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Enhanced Viewer & Browser

Replace your PACS browser with AI-powered insights.

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For Clinicians & Researchers

Ideal for testing clinical AI applications in the real world for research use or run regulated AI models.

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Test Your Own Models

Run open-source (for research use) or regulated AI models directly on local PACS.

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Secure & Scalable

Self-deployment designed for privacy, compliance, and ease

Technology

Built for Scale and Security

Our containerized architecture ensures rapid deployment, consistent performance, and seamless scalability.

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Standardized Data Processing

PACS-AI uses docker containers for rapid deployment and consistent environments.

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Modular Architecture

Plug-and-play AI models for different imaging modalities.

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Secure Infrastructure

End-to-end encryption data handling.

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Publications

Research in action

Explore studies and preprints behind models developed by or available through PACS-AI.

  • CathEF Study: AI-Powered Cardiac Function Analysis

    JAMA Cardiology, 2023

    Robert Avram et al.

    This groundbreaking study demonstrates the effectiveness of AI-powered analysis in cardiac function assessment, achieving remarkable accuracy while significantly reducing analysis time.

    Read the paper
  • DeepRV: Automated Right Ventricular Function from Coronary Angiograms

    European Heart Journal – Digital Health, 2026

    Fatima Zahra Fawzi et al.

    A video-based deep learning model that assesses right ventricular systolic function directly from routine coronary angiograms, removing the need for prior imaging. Developed at the Montreal Heart Institute, externally validated at UCSF, and deployed prospectively during primary PCI for STEMI.

    Read the paper
  • DeepCORO-CLIP: A Multi-View Foundation Model for Coronary Angiography

    arXiv preprint, 2026

    Sarra Harrabi et al.

    A multi-view foundation model trained with video-text contrastive learning for comprehensive coronary angiography interpretation, with external validation and publicly released code and weights.

    Read the paper
  • EchoPrime: A Multi-View Vision-Language Model for Echocardiography

    Nature, 2026

    Milos Vukadinovic et al.

    A view-informed vision-language foundation model for echocardiography that interprets every video in a complete study rather than a single view, using contrastive learning and retrieval-augmented interpretation.

    Read the paper
  • PanEcho: Complete AI-Enabled Echocardiography Interpretation

    JAMA, 2025

    Gregory Holste et al.

    A view-agnostic multi-task model that performs the full range of echocardiographic reporting tasks from a single pass, validated internally and across four external cohorts, and publicly released.

    Read the paper
  • CardioSyntax: End-to-End SYNTAX Score Prediction from Angiography

    arXiv preprint, 2024

    Alexander Ponomarchuk et al.

    An automatic method for estimating the SYNTAX score of coronary disease severity from multi-view angiography video, published together with a purpose-built dataset and benchmark.

    Read the paper
View all publications

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Research access

Free for research and evaluation

Available at no cost to clinicians, researchers, and institutions evaluating AI in medical imaging.

Research Use

Ideal for academic and research institutions exploring AI in medical imaging.


Free

Research license


Access to research-focused AI models

Data collection tools

Research collaboration support

Academic publication rights

Technical documentation access

* Non-FDA/Health Canada approved models. For research purposes only.

Contact us

Frequently Asked Questions (FAQ)

You have questions? We have the answers!

Need more details? Get in touch with our team!

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