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Odin Medical Technologies

odinmed.com

Stage

Acquired | Acquired

Valuation

$0000 

About Odin Medical Technologies

Odin provides small and open intraoperative real-time MRI system for neurological surgeries

Headquarters Location

826 Coal Creek Circle

Louisville, Colorado, 80027,

United States

720-890-3200

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Odin Medical Technologies Patents

Odin Medical Technologies has filed 1 patent.

The 3 most popular patent topics include:

  • Hydraulic actuators
  • Hydraulics
  • Lifting equipment
patents chart

Application Date

Grant Date

Title

Related Topics

Status

3/30/2018

3/2/2021

Hydraulics, Road infrastructure, Hydraulic actuators, Lifting equipment, Vertical transport devices

Grant

Application Date

3/30/2018

Grant Date

3/2/2021

Title

Related Topics

Hydraulics, Road infrastructure, Hydraulic actuators, Lifting equipment, Vertical transport devices

Status

Grant

Odin Medical Technologies Frequently Asked Questions (FAQ)

  • Where is Odin Medical Technologies's headquarters?

    Odin Medical Technologies's headquarters is located at 826 Coal Creek Circle, Louisville.

  • What is Odin Medical Technologies's latest funding round?

    Odin Medical Technologies's latest funding round is Acquired.

  • Who are the investors of Odin Medical Technologies?

    Investors of Odin Medical Technologies include Medtronic, Star Ventures, Pitango Venture Capital and Walden Israel Venture Capital.

  • Who are Odin Medical Technologies's competitors?

    Competitors of Odin Medical Technologies include Quality Electrodynamics, Intellirod Spine, Ortho Kinematics, Tursiop Technologies, Kjaya and 8 more.

Compare Odin Medical Technologies to Competitors

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Kjaya is a company that received a SBIR Phase I grant for a project entitled: Semi-Autonomous Adaptive Neural and Genetic Segmentation of Medical Images. Their Phase I project will implement a physician-assisted, real-time adaptive system for the segmentation of anatomical structures in 3D medical image data. Medical image segmentation seeks to change the representation of an anatomical structure, making it more easily analyzed. Because of the extreme variability of these structures in biological systems, current idiosyncratic manual methods currently in use are tedious, time consuming, and error prone. Image segmentation cannot in general be programmatically solved. The proposed system is a Neural Network (NN) based adaptation of the individual data using parallel Graphics Processing Units (GPUs) and coupled with a Genetic Algorithm (GA) based adaptation across GPU cores. The system will build a diagnostically useful segmentation of the anatomical feature within seconds from an area of interest outlined by a physician using a Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) scan. Fast growth in medical imaging overwhelms available diagnosticians. An intuitive and inexpensive system to quickly and accurately deliver diagnostic relevant segmentation of medical images offers tremendous commercial value. Currently, each scan requires approximately 50 minutes of manual preparation. The diagnosis and treatment of an estimated 20 percent of diseases benefit from medical imaging. Newer scanning technologies have increased in resolution, but such techniques have not made segmenting easier or faster. The proposed method will enable more diagnostics to be done with the quality controlled directly by physicians.

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