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Welcome to Virasoft. The "One-Stop Solution" Hub  for Clinical Pathology and Research Labs

Innovating diagnostic excellence and enhancing laboratory efficiency through a broad spectrum of digital pathology and AI-powered solutions.

Discover Virasoft Solutions & video
CONTACT LINKEDIN YOUTUBE INSTAGRAM
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Our Solutions

  • Workflow Solutions
    Workflow Solutions
    Virasoft’s APLIS equips pathology laboratories to manage the entire workflow via barcode printers, accession numbers, and barcode tracking numbers. Virasofts CE-IVD certified IMS is a web-based application that allows pathologists to store, manage, and annotate whole slide images from any scanner
    DISCOVER WORKFLOW SOLUTIONS
  • AI-Based Algorithms
    AI-Based Algorithms
    AI-based decision support algorithms to help pathologists improve diagnostic accuracy and make quicker decisions at their pathology and research labs.
    DISCOVER AI-BASED ALGORITHMS
Virasoft Academic Platforms

Virasoft Academic Platforms

Explore Virasofts advanced academic platforms designed for the future of pathology. 

Virasoft’s academic solutions are consisted of:

Our academic platforms bring instructors and students together with scanned whole slide images (WSIs), assignments and lectures.

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Why Choose Virasoft?

Why Choose Virasoft?
“One-Stop Solution” hub for pathology and research labs
“One-Stop Solution” hub for pathology and research labs
Customizable and modular solutions
Customizable and modular solutions
Compatible with all scanner devices
Compatible with all scanner devices
Extensive clinical expertise
Extensive clinical expertise
Seamless reviewing, sharing, and storing of images and reports
Seamless reviewing, sharing, and storing of images and reports
De-identification capability to anonymize cases
De-identification capability to anonymize cases
Improve and digitize consultation process
Improve and digitize consultation process
24/7 expert level support
24/7 expert level support

AI and digital pathology play a crucial role in
minimizing diagnostic errors in pathology.

Traditional methodology

  • Unchanged Practices

    • The practice of pathology has mostly stayed the same since the early 20th century.

  • Subjective Interpretations

    • Open to interpretation leads to a high interobserver and intraobserver variation rate.

  • Limited Expertise

    • Uneven distribution of pathologists, resulting in inconsistent access to specialized knowledge.

Digital transformation

Digital Workflow in Pathology Laboratories

VIRASOFT’S WORKFLOW AND
DIAGNOSTIC USAGE

  • Workflow Solutions:<br> IMS & APLIS Workflow Solutions:
    IMS & APLIS
    400000 / year

    cases reported

  • AI-Powered Decision<br> Support AI-Powered Decision
    Support
    30000 / year

    algorithms used

  • Telepathology Telepathology
    20000 / year

    cases consulted

  • Academic Academic
    15000 / total

    students attended

Our News

Virasoft Partners with Pathoteam Diagnostic to Redefine AI-P
Virasoft Partners with Pathoteam Diagnostic to Redefine AI-Powered Pathology in Romania

Virasoft and Pathoteam Diagnostic join forces to set new standards in pathology with advanced AI solutions.
This collaboration represents a significant milestone in Virasoft’s mission to provide innovative AI-powered pathology solutions to laboratories around the globe.

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NEW feature in the latest version of Virasoft’s APLIS, Virap
NEW feature in the latest version of Virasoft’s APLIS, Virapis!

A New Era of Synoptic Reporting in Smear Diagnostics: The Bethesda Synoptic Checklist
This enhancement is designed to standardize smear reports and provide greater accuracy in cytology diagnostics.

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Join us at USCAP’24
Join us at USCAP’24

We are excited for USCAP 2024 and looking forward to meeting you there. We are inviting you to our Booth #1049, 4 poster and 1 platform sessions with Virasoft AI-powered decision support products and co-authored

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Tubule-U-Net: a Novel Dataset and Deep Learning-Based Tubule
Tubule-U-Net: a Novel Dataset and Deep Learning-Based Tubule...

Virasofts research article, "Tubule-U-Net: A novel dataset and deep learning-based tubule segmentation framework in whole slide images of breast cancer," published in Scientific Reports (Nature, 2023), ranked among the top 100 most downloaded cancer research papers of the year.

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