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Chest CT Segmentation

The challenge

  • An industry leading medical device company required the capability to automatically generate an accurate 3d model of complex patient-specific anatomies
  • The anatomical model was needed for planning challenging surgical navigation procedures
  • The pre-existing solution was slow and not robust, requiring extensive and time-consuming manual editing by the interventionist

Our approach

  • RSIP Vision leveraged its deep-learning based 3d CT auto-segmentation technology to deliver a customized, fast, robust, production quality solution

The outcome

  • Core module integrated in client platform and is in clinical use
  • Used in 1000’s of cases in hospitals worldwide
  • >99% segmentation success rate
  • 1mm-level segmentation resolution
  • 30 seconds running time on full-sized chest CT scan

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3D Reconstruction for Heart Chambers

Orthopedic Surgery Planning & Navigation

Auto-FAC & quality grading for Cardiac Ultrasound

Endoscopic Video Analysis

Surgical Stages Recognition

Cell Segmentation & Abnormality Risk Estimation

3D Reconstruction for Heart Chambers

Orthopedic Surgery Planning & Navigation

Auto-FAC & quality grading for Cardiac Ultrasound

Endoscopic Video Analysis

Surgical Stages Recognition

Cell Segmentation & Abnormality Risk Estimation

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Created by Shmulik

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