Viz HDS

by Viz.ai  · Based in United States → — The leader in AI-powered disease detection and intelligent care coordination.
Neurology Neurosurgery Radiology

Contact for pricing
Regulatory Status Disclosed

Overview

Viz HDS, also known as Viz ICH+ and Viz Volume Plus, is an AI-powered solution developed by Viz.ai for the analysis of non-contrast CT images. It is designed to automatically label, visualize, and quantify segmentable brain structures, specifically focusing on intracranial hyperdensities, lateral ventricles, and midline shift. This tool aids physicians in the rapid assessment and management of conditions such as intracranial hemorrhage by providing automated volume calculations and color-coded overlays. It integrates seamlessly into existing clinical workflows by sending results in DICOM format back to PACS and is part of the broader Viz.ai One platform, which leverages over 50 FDA-cleared AI algorithms to accelerate diagnosis, streamline workflows, and support faster treatment decisions across various medical conditions. The user’s note mentioned ‘physician directory’ for Viz HDS; however, all available information indicates that Viz HDS/Viz ICH+ is a medical imaging AI tool and not a physician directory service.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-powered detection and quantification of intracranial hyperdensities
  • Measurement and segmentation of hyperdense collections on non-contrast CT images
  • Color-coded overlays for efficient decision-making
  • Automated total volume calculation for selected collections
  • Displays left and right ventricular volumes and midline shift
  • Results sent in DICOM format back to PACS for seamless integration
  • Real-time alerts and intelligent care coordination
  • Available on mobile and desktop devices
  • Integration with EHR and PACS systems
  • Supports AHA 'Get With the Guidelines' standards for ICH care

Use Cases

  • Accelerating diagnosis and treatment decisions for intracranial hemorrhage (ICH)
  • Streamlining interhospital transfer (IHT) for ICH patients
  • Improving workflow for radiologists, neurologists, and neurosurgeons
  • Assessing severity, monitoring progression, and planning treatment strategies for brain bleeds
  • Automating ICH scoring and documentation
  • Enhancing multidisciplinary care team collaboration

What Physicians Need to Know

Brain CT Analysis (Non-Contrast CT)
Viz HDS is specifically designed for automatic labeling, visualization, and quantification of segmentable brain structures from Non-Contrast CT (NCCT) head scans. It analyzes intracranial hyperdensities, lateral ventricles, and midline shift, providing volume measurements.
Stroke Detection Speed (Hemorrhagic)
Viz ICH, part of the Viz Hemorrhage suite which includes Viz HDS functionalities, automatically identifies suspected intracerebral hemorrhage (ICH) strokes on non-contrast CT imaging and alerts on-call stroke teams in less than 30 seconds, saving an average of 37 minutes from picture to alert compared to standard care.
Large Vessel Occlusion Detection
While Viz HDS focuses on hemorrhagic strokes, the broader Viz.ai platform includes Viz LVO, an AI algorithm that automatically detects and triages suspected large vessel occlusions (LVOs) in ischemic stroke cases, reducing time to treatment.
Triage Prioritization Speed
The Viz.ai platform, through its rapid analysis and mobile alerts, significantly improves triage prioritization. For LVOs, it has been shown to reduce door-in-door-out (DIDO) times by nearly 50% and decrease critical stroke care metrics like door-to-transfer and door-to-puncture.
ASPECTS Score Automation
Viz.ai is integrating Avicenna.AI's CINA-ASPECTS tool into the Viz.ai Oneu2122 platform, which automatically assesses the Alberta Stroke Program Early CT Score (ASPECTS) from CT brain images, providing an objective measure of stroke severity.
Mobile Notification System
Viz.ai utilizes a HIPAA-compliant mobile notification system that sends alerts to care teams, allowing them to view high-fidelity images and patient information on their mobile devices. Users can customize notification settings, including push/SMS and sounds, and override silent modes.
Physician Tip

Always review the AI-generated output from Viz HDS alongside the patient's original images for comprehensive assessment. Leverage the automated measurements for intracranial hyperdensities, lateral ventricles, and midline shift to consistently assess severity, monitor progression, and plan treatment strategies. Utilize the mobile access for rapid decision-making and seamless care coordination among multidisciplinary teams, especially in time-sensitive stroke cases. Integrate with your Electronic Health Record (EHR) system to gain relevant contextual patient data and streamline workflows.

The Viz.ai One platform, which hosts Viz HDS, offers expanded interoperability capabilities. It integrates with Electronic Health Record (EHR) systems (e.g., Epic, Cerner), Picture Archiving and Communication Systems (PACS), and radiology worklist systems to streamline clinical workflows and provide real-time patient data. The system processes and exports medical image data in DICOM format. Viz.ai is also integrating third-party AI tools, such as Avicenna.AI's CINA-ASPECTS, to enhance its neurovascular solution.

Details

Category Neurology AI
Pricing Contact for pricing — Custom enterprise pricing; subscription-based SaaS model
DeploymentCloud-based
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

Viz HDS (also referred to as Viz Volume Plus and Viz ICH+) received FDA 510(k) clearance (K232363) on February 5, 2024. It is intended for automatic labeling, visualization, and quantification of segmentable brain structures from non-contrast CT head scans, specifically for intracranial hyperdensities, lateral ventricles, and midline shift.

Integrations
EHR Not specified
Specialties Neurology, Neurosurgery, Radiology

What the Web Says

Viz.ai (also referred to as Viz HDS, Viz.ai One) is an AI-powered medical imaging and care coordination platform primarily used in hospitals and health systems to accelerate the diagnosis and treatment of time-sensitive conditions like stroke, pulmonary embolism, and aortic dissection. It leverages AI algorithms to analyze medical images, detect critical findings, and alert care teams in real-time, aiming to reduce time-to-treatment and improve patient outcomes. The platform is widely deployed in nearly 2,000 hospitals across the U.S. and Europe and has over 50 FDA-cleared algorithms.

Overall: Positive

Strengths

  • Significantly reduces time-to-treatment for critical conditions like stroke, PE, and aortic dissection by providing rapid detection and alerts.
  • Enhances care coordination and communication among multidisciplinary care teams (e.g., radiology, neurology, interventional radiology) through real-time image sharing and secure mobile communication.
  • Offers a comprehensive platform with over 50 FDA-cleared algorithms, providing a single solution for various disease states across multiple departments.
  • Integrates seamlessly with existing hospital systems like PACS and EHR, ensuring efficient workflows and easy access to information.
  • Backed by strong clinical evidence and third-party verification, distinguishing it from other AI vendors with unproven claims.
  • Non-technical users found the onboarding process relatively smooth with minimal IT overhead.

Limitations

  • Enterprise-only pricing makes it inaccessible to individual physicians.
  • Some users have reported issues with Single Sign-On (SSO) and user management, requiring tweaks.
  • Vendor support has been described as responsive but not always timely, sometimes requiring follow-up.
  • Occasionally flags subsegmental PEs that are not clinically significant, though sensitivity is generally valued.
  • Not a general clinical decision support tool; it's specialized imaging infrastructure and won't help with tasks like looking up drug doses or generating differentials.
  • The hypertension feature, though approved, is a different use case than existing Viz.ai software, which can be a point of confusion.

Based on reviews from: Clinical AI Report, CREAITIQUE, G2, Comparably, The Silicon Review, FeaturedCustomers, Reddit, PubMed Central (PMC), UC Davis Health, Forbes, Stock Titan, SoftwareWorld, FDA

Last updated: 2026-07-21

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Press & Coverage

Viz.ai
Viz.ai Launches Viz Pulmonary Suite, the First Comprehensive AI-Powered Solution Dedicated to Pulmonary Care Delivery
Viz.ai announced the launch of its Viz Pulmonary Suite, an AI-powered solution designed to improve pulmonary care by reducing time to treatment and improving patient outcomes. This suite is the first comprehensive AI solution for pulmonary care.
2026-05
Viz.ai / Business Wire
Viz.ai Announces Strategic Collaboration to Expand Access to AI-Powered Subdural Hemorrhage Care
Viz.ai is collaborating with Johnson & Johnson to expand access to its AI-powered Subdural Hemorrhage software solution, which automates the detection, labeling, and quantification of subdural collections. This aims to streamline care pathways for suspected chronic subdural hematoma.
2026-04
Viz.ai / Business Wire
Viz.ai Expands into Neurodegenerative Disease with Cortechs.ai Collaboration
Viz.ai has partnered with Cortechs.ai to integrate NeuroQuant and NeuroQuant MS into the Viz.ai platform, extending Viz Neuro Suite into neurodegenerative diseases like multiple sclerosis. This collaboration aims to provide quantitative neuroimaging for better patient identification and management.
2026-07
Viz.ai
Viz.ai Achieves ISO/IEC 42001 Certification, Setting the Standard for Agentic AI in Healthcare
Viz.ai has received ISO/IEC 42001 certification, validating its enterprise-grade AI governance framework for safe and scalable agentic clinical workflows. This certification underscores their commitment to responsible AI in healthcare.
2026-05
Viz.ai
Viz.ai and National Rural Health Association Launch Initiative to Bring AI-Powered Detection and...
Viz.ai and the National Rural Health Association have launched an initiative to help rural hospitals detect suspected conditions earlier, coordinate care faster, and serve more patients through AI-powered detection and care coordination.
2026-04
Viz.ai
Viz.ai Wins Gold Edison Awardu2122 for Advancing AI-Driven Clinical Workflows to Improve Hemorrhage...
Viz.ai received its fourth consecutive Gold Edison Award for its role in advancing AI-driven clinical workflows, specifically for improving hemorrhage care. This award highlights their impact on AI-driven decision-making at the point of care.
2026-04
PMC (PubMed Central)
Machine Learning-Enabled Medical Devices Authorized by the US Food and Drug Administration in 2024: Regulatory Characteristics, Predicate Lineage, and Transparency Reporting
This peer-reviewed article analyzes FDA-authorized machine learning-enabled medical devices in 2024, including Viz HDS (K232363), noting its 510(k) clearance for stroke triage. The study examines regulatory pathways, predicate lineage, and transparency reporting for these devices.
2025-12
FDA
Viz HDS, Viz Volume Plus, Viz ICH+ K232363
The FDA 510(k) clearance document for Viz HDS (K232363) details its intended use for automatic labeling, visualization, and quantification of segmentable brain structures from Non-Contrast CT head scans. It is indicated for analyzing intracranial hyperdensities, lateral ventricles, and midline shift.
2024-02

Videos

Product demos, reviews, and walkthroughs for Viz HDS.

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Frequently Asked Questions

Viz HDS is designed for automatic labeling, visualization, and quantification of segmentable brain structures from non-contrast CT scans, specifically focusing on intracranial hyperdensities, lateral ventricles, and midline shift. It automates the manual process of identifying and quantifying these structures, and the broader Viz.ai platform integrates with EHR, PACS, and radiology worklist systems to streamline workflows and facilitate real-time data access.
Yes, Viz HDS (also referred to as Viz ICH Plus and Viz Volume Plus) has received FDA 510(k) clearance for its neurological applications, including the analysis of intracranial hyperdensities, lateral ventricles, and midline shift. Viz.ai maintains a comprehensive HIPAA compliance program, along with SOC 2 Type II, ISO 27001, ISO 27701, and ISO 27799 certifications, to ensure robust patient data privacy and security.
Leading alternatives to Viz.ai in the stroke AI market include RapidAI and Brainomix. While all aim to enhance stroke diagnosis and care, studies have indicated differences in performance, with some research suggesting RapidAI may outperform Viz.ai in detecting certain conditions like medium and large vessel occlusions.
Viz.ai typically operates on a subscription-based pricing model. While specific figures can vary, a CMS document referenced a potential annual cost of $25,000, with pricing likely tiered based on factors such as the type of stroke center (e.g., primary vs. comprehensive).
Viz HDS is intended as an assistive tool, and its output should always be reviewed by a physician alongside the patient's original images; it does not replace a neurologist's expert interpretation. Limitations can include potential biases inherent in AI algorithms and variations in accuracy compared to other AI solutions for specific neurological findings.
Viz HDS, along with other Viz.ai neurovascular algorithms, aims to improve patient outcomes by automating the identification and quantification of critical brain structures and pathologies, such as intracranial hyperdensities, subdural hematomas, and large vessel occlusions. This automation facilitates faster assessment, more timely treatment decisions, and enhanced care coordination among multidisciplinary teams.
Physicians using AI tools like Viz HDS retain the ultimate responsibility for patient care, as the device output is intended to be reviewed by a physician. The regulatory landscape for AI in healthcare is evolving, with FDA oversight for diagnostic tools and HIPAA for data handling, requiring adherence to specific policies, documentation, and staff training.

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Suggest an Edit → | Last Verified: 2026-04-21 | First Added: 2026-04-21

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