Our Mission

Development of an open-source musculoskeletal imaging database for researchers and surgeons to study and improve on the surgical outcomes with iterative planning

ABOUT US

Vent Creativity is a machine-learning powered auto-segmentation tool for researchers and medical professionals. Our patented AI platform technology allows users to collect and analyze meaningful data on population-based studies. With the click of a button, you can have access to segmented and landmarked DICOM files to push forward your research and unlock new discoveries! Licensed products are available to do population based landmark studies, plan specific surgery types, and conduct multi-center clinical outcomes studies

 
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VENT products are currently for research use only and are not commercially available for clinical use in the USA

 

Auto-segmentation

Contact us for your segmentation needs for various musculaskeletal structures. This feature is not for clinical use. 

Auto-Landmarking

Contact us for auto-landmarking, a machine-learning feature that automatically detects relevant points, lines, and planes. Population based analysis will be available for bone types in stages.

Surgical Planning Support

Work in Progress

 

Vent Creativity is excited to announce that our first patent was issued today on medical imaging-based 3D visualization, surgical planning, and robotic/nav guided surgery applications (USP 10,937,542) . The patent covers all medical applications, but specific examples for orthopaedics include:

Auto-segmentation:

  • Our patent covers AI-based CT and MRI based auto-segmentation, including bone density mapping for planning implant or soft tissue reconstruction for optimal fixation. For example, in most cases, the unicondylar knee or shoulder replacements primarily fail due to poor bone purchase. Our patent provides a potential solution for this problem with unique surgical planning strategies. 

Auto-landmarking and patient clustering:

  • We group patients based on landmarks and other parameters to determine best surgical intervention strategies. For example, we are currently developing a system to determine the optimal implant positions, sizes, and joint-gap calculations to plan surgery prior to a single cut.

  • The patent also claims surgical outcomes-based analysis to potentially improve manual and robotic surgeries.

  • Our patent covers Activities of Daily Living (ADL) based kinematic modeling for optimal implant or sports medicine intervention. This includes soft-tissue simulation to adjust kinematics solutions to ADLs for different patient types. This option will also allow surgeons to adjust surgery plans on the go. 

Robotic and additive manufacturing applications:

  • Our patent covers the incorporation of VR/AR based surgery visualization tools. This will facilitate better surgical interaction with 3D bone and soft-tissue models.

  • The patent covers VENT’s innovative approach for 3D printed cutting guides, which would allow surgical plans to potentially achieve the level of accuracy normally seen in robotic surgeries. This is ideal for ASCs with limited physical space and budget.

  • The patent covers a wide range of remote surgery options, include:

    • 3D printed bones with unique coloring that show areas to cut;

    • Low-cost tactile feedback for robotic surgeries with physical bone substitute;

    • Navigation block holders that are incorporated into the 3D printed bone;

    • 3D printed bone and cutting tool interaction mirrored by a robot in the OR;

    • Optional removable guide features to overlay on the 3D bone to prevent soft-tissue damage;

    • 100% visibility of the 3D printed bone as the robot performs MIS surgery.

  • Lastly, the patent includes surgical training methodologies with VR/AR and 3D printed models for pre-op practice.

In short, this patent - together with VENT’s AI-based technology - could dramatically reduce the costs and planning time associated with current medical procedures. With advances in telecommunications, robotic surgery can be performed remotely and with high quality visualization.

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