Unlock your data
and supercharge your MRI operations

Quantivly MRI

Vendor Agnostic

Fully Queryable

Easily integrated

Developed at

Quantivly developed at Boston Child Hospital

Can you capture the details of your MRI workflow?

Quantivly Disclaimer

Manual logs are expensive, inefficient, error-prone and not sustainable.

Quantivly Data
Quantivly Operational Insight Quantivly Operational Insight
  • Why is scanner 3 always running behind ?
  • Why are some technologists more agile than others ?
  • Why are patients complaining about delays ?
  • How can we image more patients ?

We unlock data to answer your questions

It's not just about what was scheduled
It's about what really happened

We built a unified interface to query your MRI operations




Our platform extracts, cleans and harmonizes the information from MRI images and builds a unifying, fully queryable ontology.

Quantivly - Unified Metadata Layer
  • Cleans and harmonizes image metadata
  • Augments and interprets with AI

    Quantification of motion, detection of repeats, labeling of organs, ...

  • Builds a query-able ontology

You can finally ask detailed questions of your data

KPIs only tell you where you are.

Taking action requires a 360 view

Quantivly Measurement Capabilities

Previously unattainable measurement capabilities

  • Effective protocol duration
  • True inter-patient time
  • Active imaging time
  • Technologist agility
  • Repeat rate
  • and 20+ more metrics
Quantivly Measurement Capabilities

Amazing metadata granularity

Instant access to 30+ technical parameters of images: TE, TR, NEX, SAR, resolution, sequence name, etc

Ready for any question or pattern analysis.

Quantivly Measurement Capabilities

Compare whatever and however you want

  • Scanners
  • Protocols
  • Sequences
  • Body systems
  • Patient demographics
  • Technologists
  • Physicians
  • Time of the day

“If you can’t measure it, you can’t improve it”

Examples of Applications

Quantivly Application Example
Get an instant overview of all your protocols and imaging parameters, for each scanner.
Quantivly Application Example
Don't guess what the bottlenecks are. Identify, from your data, which acquisitions are longest to acquire and which scans exceed their allotted time. Focus on these to have the maximum impact.
Quantivly Application Example
Automatically and robustly filter your protocols based on acquisition parameters (not protocol names!). Monitor use and drive adoption with data-driven strategies: see which scanners are running behind, identify inefficient protocols and drive adherence.
Quantivly Application Example
Use data to monitor how your MRI sequences are used. Drive adoption of your newly purchased sequence with data-driven strategies.
Quantivly Application Example
You can finally evaluate the true, effective duration of your imaging protocols - and not only their average duration, but also the variability. Identify bottlenecks (e.g., variability per technologist, per exam, etc.), drive training and reduce slot size confidently with data-driven strategies.
Quantivly Application Example
Evaluate technologist agility, i.e. their ability to maximize the active imaging ratio for each exam [magnet time/exam duration]. Drive training and maximize your overall active imaging time.
Quantivly Application Example
Measure the true inter-patient time and test different strategies with data. For example, quantify the impact of using a second detachable MR tables within your workflow. Or a third.
Quantivly Application Example
Use pattern analysis to identify patterns in delays in your data, solve bottlenecks and increase predictability.
Quantivly Application Example
Identify repeats not based on naming conventions but with machine learning and pattern analysis on image acquisition parameters. Validate the effectiveness of your purchase with data and double-down on effective investments.
Quantivly Application Example
Understand where you have available imaging time and load balance with data-driven strategies.
Quantivly Application Example
Compile detailed reports on scanner utilization to justify new capital expenses.
Quantivly Application Example
The potential is huge...
  • Check the acquisition parameter consistency in your research imaging studies
  • Extract information from the data for analysis (SAR, repeat rate, ...)
  • Collect and organize data for AI
  • Map parameters with image quality
  • Stratify the populations most at risk of motion
  • Evaluate trends in protocols evolution
  • etc.
The limit is your imagination.

Use Case: Boston Children’s Hospital

Increasing throughput and reducing sedation with data-driven strategies

  • Filtered imaging protocols based on acquisitions parameters
  • Monitored which imaging protocols were effectively used
  • Supervised and drove adoption of faster protocols with data-driven strategies
Quantivly Data-Driven Strategies

Monitoring and driving the increased number
of fast scans with data

“ The platform was key in reducing sedation by 20%, having an impact not only on the bottom line but also on the patient experience & health

Analyzing imaging workflows & bottlenecks during the COVID lock-down

Active scanner time per body system


Brain / Spine



Vent Check

Quantivly Analysis Quantivly Analysis

Our Team

Founder / CEO

Benoit Scherrer, Ph.D.
Assistant Professor in Radiology
at Harvard Medical School
Medical Advisor

Jeffrey Mendel, MD
Former Chair of Radiology
Former Chief of Radiology Informatics
Scientific Advisor

Simon K. Warfield, Ph.D.
Director of Radiology Research
at Boston Children's Hospital
Scientific Advisor

Robert MacDougall, Ph.D.
Former Director of Diagnostic Imaging Physics
at Boston Children's Hospital
Industry Advisor

Richard Stadterman
Former VP of Global R&D
at Bayer Healthcare
Product Advisor

Srikanth Mruthik
Former Global Manager
of MRI Software at GE
Sales advisor

Christopher Montoni
VP Sales with 20+ years
experience in Radiology IT
Quantivly Logo

What is under the hood?

Retire your notebook and your manual logs. We are extracting, cleaning, harmonizing and organizing all the data you need from the scanner data itself (DICOM) and from other sources.

While DICOM provides a basic standard for describing the geometry of images for radiological interpretation, it fails at providing an ontology that describes imaging exams - it was designed for a different purpose and has been incompatibly extended by different vendors.

After years of R&D, Quantivly has built an ontology that starts from DICOM and, using data intelligence and machine learning, builds upon it to construct the first real-time, unified, vendor-agnostic description of imaging exams.

You can finally ask questions of your data and unlock a new world of data analytics.

And this is just the beginning. We have an exciting roadmap.

Supported by the National Science Foundation
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