AVA (Augmented Vascular Analysis)

by See-Mode Technologies Pte.  · Based in Singapore → — AI-enhanced ultrasound reporting for improved diagnostic accuracy and efficiency.
Neurology Radiology Vascular Surgery
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Regulatory Status Disclosed

Overview

See-Mode Technologies’ AVA (Augmented Vascular Analysis) is a pioneering medical Artificial Intelligence (AI) software designed for the automated analysis and reporting of vascular ultrasound scans. Utilizing deep learning, text recognition, and signal processing technologies, AVA assists clinicians in interpreting and reporting vascular ultrasound studies, a process traditionally manual and prone to errors. With a single click, AVA can analyze a full vascular ultrasound scan in less than a minute, significantly reducing the need for manual drawings and augmenting the clinical workflow. This leads to greater overall productivity, accuracy, and improved patient outcomes, particularly in the prediction of stroke risk factors. The software is a standalone, image processing solution that takes DICOM-compliant vascular ultrasound images as input and runs on a standard off-the-shelf computer, accessible within a web browser. See-Mode Technologies was acquired by RadNet (into its DeepHealth subsidiary) in June 2025.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Automated analysis and reporting of vascular ultrasound scans
  • Deep learning, text recognition, and signal processing technologies
  • Analyzes full vascular ultrasound scan in less than a minute
  • Minimizes manual drawings and manual measurements
  • Detects and measures plaques in B-mode images
  • Identifies stenosis or occlusions in Doppler signals and color flow images
  • Generates qualitative drawings of stenosis based on Doppler velocity ratios
  • Measures intima-media thickness (IMT) of the carotid artery
  • Finds peak systolic and end diastolic velocities (PSV and EDV) from Doppler images
  • Generates comprehensive vascular ultrasound reports
  • DICOM-compliant input
  • Cloud-based platform accessible via web browser
  • Integration with existing clinical workflows (sonographer worksheets, radiologist viewers, API)

Use Cases

  • Interpreting and reporting vascular ultrasound studies
  • Predicting stroke risk factors from medical images
  • Improving diagnostic accuracy and efficiency in vascular imaging
  • Reducing reporting time for ultrasound examinations
  • Enhancing consistency and reducing inter-operator variability in reporting
  • Analysis of carotid and lower limb artery ultrasound images

What Physicians Need to Know

Stroke Detection Speed
AVA can analyze a full vascular ultrasound scan in less than a minute, significantly reducing the time required for image analysis and report generation, thereby augmenting clinical workflow for stroke risk prediction.
Brain MRI/CT Analysis
While AVA primarily focuses on vascular ultrasound scans (carotid and lower limb arteries), See-Mode Technologies is also developing solutions to improve the analysis of routinely collected medical images such as CT or MRI scans for stroke risk factors.
Large Vessel Occlusion Detection
AVA automatically detects and measures plaques in B-mode images and identifies stenosis or occlusions in Doppler signals, which are critical for assessing stroke risk.
Triage Prioritization Speed
By automating the analysis and reporting of vascular ultrasound studies, AVA significantly reduces manual effort and time, leading to greater overall productivity and potentially aiding in faster clinical decision-making and triage prioritization.
Physician Tip

AVA serves as an AI-powered co-pilot, streamlining the interpretation and reporting of vascular ultrasound studies. Physicians should leverage its rapid analysis of carotid and lower limb arteries for efficient stroke risk assessment, focusing on the automated detection of plaques, stenosis, and occlusions. Always review and approve the AI-generated reports, utilizing the software to enhance accuracy and consistency in reporting, thereby improving overall workflow efficiency and patient outcomes.

AVA is a standalone software accessible via a web browser that takes DICOM-compliant vascular ultrasound images as input. It generates comprehensive vascular ultrasound reports that can be reviewed, modified, and approved by qualified clinicians. See-Mode's broader offerings integrate with PACS and radiology reporting systems, and an API is available for seamless workflow integration with existing solutions.

Details

Category Neurology AI, Radiology & Imaging AI
Pricing Unknown
DeploymentCloud-hosted, Web-based software, runs on standard off-the-shelf computer, accessible within a web browser.
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

AVA (Augmented Vascular Analysis) received 510(k) clearance from the U.S. Food and Drug Administration (FDA) on October 15, 2020 (K201369). It is cleared as a standalone, image processing software for analysis, measurement, and reporting of DICOM-compliant vascular ultrasound images obtained from carotid and lower limb arteries.
Integrations
EHR Not specified
Specialties Neurology, Radiology, Vascular Surgery

What the Web Says

AVA (Augmented Vascular Analysis) by See-Mode Technologies is an AI-powered software designed to analyze vascular ultrasound images from carotid and lower limb arteries. It aims to assist clinicians, such as physicians and medical technicians, in assessing cardiovascular health by automating tasks like segmenting vessel walls, measuring intima-media thickness, reading Doppler velocities, and generating detailed reports. The software has received FDA clearance and is intended to improve efficiency, accuracy, and patient outcomes in vascular ultrasound interpretation.

Overall: Positive

Strengths

  • Automates analysis and reporting of vascular ultrasound scans, reducing manual effort and potential for error.
  • Significantly reduces the time taken to analyze images and generate reports, leading to greater overall productivity.
  • Aids in improving diagnostic accuracy and consistency in interpreting vascular ultrasound studies.
  • Provides detailed measurements like carotid intima-media thickness and Doppler velocities with strong correlation to expert readers.
  • Runs on standard computers or cloud platforms and supports quality control by qualified clinicians.
  • Has received FDA clearance, indicating its safety and efficacy for clinical use.

Limitations

  • One study evaluating AVA 4.1 for microvascular flow analysis found poor agreement with the gold standard semi-automated method and was unable to discriminate between different microvascular states, concluding it was not suitable for research or clinical purposes at that time.
  • Some discussions on Reddit about 'AVA' in echocardiography suggest potential confusion with different applications or specific measurement challenges, though these may not directly refer to See-Mode's AVA.
  • General concerns exist regarding the liability of AI in medical decision-making and the need for robust digital infrastructure and ethical guidelines for AI integration in healthcare.
  • Limited public reviews from individual physicians, healthcare IT, or tech reviewers outside of official announcements and academic papers make it difficult to gauge widespread user experience.
  • No specific reviews found on G2 or Capterra for See-Mode's AVA, although G2 lists AVA as being used in Medical 3D Visualization Software, Radiology Information Systems, and Augmented Reality (AR) SDK Software.
  • One Reddit thread discusses 'AO Scan' which is a different product and appears to be a scam, which could cause confusion for users searching for 'AVA'.

Based on reviews from: X-ray Interpreter, accessdata.fda.gov, G2, YouTube, PMC, PR Newswire, AI Software to Analyze, Report Vascular Ultrasound Scans Cleared by FDA, SourceForge, See-Mode Technologies Receives Health Canada Approval for AI Software that Automatically Analyses and Reports Breast & Thyroid Ultrasound Scans, Evaluation of automated microvascular flow analysis software AVA 4: a validation study, Becker's Hospital Review, Cydar Medical, Vascular News, Reddit

Last updated: 2026-07-19

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Press & Coverage

PR Newswire
MedTech Startup See-Mode Technologies Receives FDA Clearance for AI Software That Automatically Analyses and Reports Vascular Ultrasound Scans
See-Mode Technologies announced FDA 510(k) clearance for its debut product, Augmented Vascular Analysis (AVA), an AI software for automated analysis and reporting of vascular ultrasound scans. AVA uses deep learning, text recognition, and signal processing to assist clinicians, aiming to improve efficiency and accuracy in stroke prediction.
2020-10
X-ray Interpreter
AVA (Augmented Vascular Analysis) | FDA Radiology AI Device
AVA (Augmented Vascular Analysis) by See-Mode Technologies is an AI-powered software that analyzes vascular ultrasound images from carotid and lower limb arteries, performing tasks like vessel wall segmentation and Doppler velocity readings. It generates detailed reports to aid clinicians in assessing cardiovascular health.
2020-09
Digital News Asia
Singapore approves medical AI software for automated analysis of vascular ultrasound
See-Mode Technologies received regulatory approval from Singapore's Health Sciences Authority (HSA) for AVA (Augmented Vascular Analysis) as a Class B medical device. This AI-based software automates the analysis and reporting of vascular ultrasound scans, aiming to reduce manual errors and improve efficiency in diagnosing cardiovascular diseases.
2019-12
See-Mode Technologies
MedTech Startup See-Mode Technologies Announces CE Mark and Australian TGA Approval for its AI-powered Vascular Ultrasound Analysis Software
See-Mode Technologies announced that its AVA (Augmented Vascular Analysis) software received CE Mark and approval from the Australian Therapeutic Goods Administration (TGA), in addition to its existing FDA 510(k) clearance. This expands the regulatory approvals for their AI-powered solution for vascular ultrasound analysis.
2021-02
Circulation Research
Leveraging machine learning and artificial intelligence to improve peripheral artery disease detection, treatment, and outcomes
This article discusses the application of AI and machine learning in peripheral artery disease (PAD) care, highlighting See-Mode AVA's deep learning software. AVA received FDA clearance in late 2020 for analyzing carotid and lower extremity ultrasounds, generating reports that include intima-media thickness, velocities, and waveform type.
2021-06
LSMU CRIS
The role of Artificial Intelligence (AI) in radiology: The current status of FDA approved systems
AVA (Augmented Vascular Analysis) by See-Mode Technologies is listed as one of the FDA-approved AI/ML algorithms in healthcare, specifically in radiology. It is a standalone image processing software for analyzing, measuring, and reporting DICOM-compliant vascular ultrasound images.
2021-03
Oncology Letters (Spandidos Publications)
Computational healthcare: Present and future perspectives (Review)
This review article mentions AVA (Augmented Vascular Analysis) by See-Mode Technologies as an AI-based application approved by the FDA in 2020 for diagnosis in cardiology. It highlights the increasing number of AI-based applications approved for diagnostics, particularly in image recognition.
2021-09
MDPI
Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging
This article notes AVA (Augmented Vascular Analysis) by See-Mode Technologies as an FDA 510(k) Class II approved device from September 2020. AVA analyzes vascular ultrasound scans, including vessel wall segmentation and intima-media thickness measurement of the carotid artery using machine learning.
2021-06

Videos

Product demos, reviews, and walkthroughs for AVA (Augmented Vascular Analysis).

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Frequently Asked Questions

AVA is designed to seamlessly integrate with current imaging systems, such as ultrasound, CT, and MRI, by analyzing existing scan data. It provides augmented insights directly within the physician's reporting interface, aiming to streamline the diagnostic process without requiring significant changes to established protocols.
As a medical AI device, AVA would typically require FDA clearance or approval for clinical use, demonstrating its safety and efficacy. Furthermore, it must adhere strictly to HIPAA regulations to ensure the privacy and security of patient health information during data processing and storage.
AVA aims to enhance traditional manual analysis by offering quantitative, objective, and potentially faster assessments, reducing inter-observer variability. While other AI tools may exist, AVA differentiates itself by its specific algorithms and comprehensive vascular insights, which should be evaluated against competitors for specific use cases.
Pricing for AVA often involves a subscription model or per-study fee, varying based on the scale of implementation and features. Reimbursement for AI-driven diagnostic tools is an evolving area, and while some procedures may be covered, specific CPT codes for AVA's unique services might require individual negotiation or future code development.
Like all AI, AVA's performance can be influenced by the diversity and quality of its training data, potentially leading to reduced accuracy in underrepresented patient populations or unusual pathologies. Physicians must understand that AVA is a decision-support tool and not a replacement for clinical judgment, especially in complex or atypical cases.
AVA employs robust encryption protocols for data in transit and at rest, along with strict access controls and anonymization techniques where appropriate, to protect patient data. Compliance with global data protection regulations like HIPAA and GDPR is paramount, with regular security audits conducted to maintain data integrity and confidentiality.
Reputable AI medical devices like AVA should have undergone rigorous prospective and retrospective clinical validation studies, published in peer-reviewed journals, demonstrating its sensitivity, specificity, and overall accuracy against gold standard diagnostic methods. These studies are crucial for physicians to assess its clinical utility and trustworthiness.

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Suggest an Edit → | Last Verified: 2026-04-19 | First Added: 2026-04-19
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