We present a novel methodology to detect imperfect bilateral symmetry in CT of human anatomy.
Suboptimal interaction with patient data and challenges in mastering 3D anatomy based on ill-posed 2D interventional images are essential concerns in image-guided therapies.
For C-arm repositioning to a particular target view, the recorded C-arm pose is restored as a virtual object and visualized in an AR environment, serving as a perceptual reference for the technician.
In this work, we present a method to automatically detect anatomical landmarks in X-ray images independent of the viewing direction.
In percutaneous orthopedic interventions the surgeon attempts to reduce and fixate fractures in bony structures.
no code implementations • 4 Jan 2018 • Javad Fotouhi, Clayton P. Alexander, Mathias Unberath, Giacomo Taylor, Sing Chun Lee, Bernhard Fuerst, Alex Johnson, Greg Osgood, Russell H. Taylor, Harpal Khanuja, Mehran Armand, Nassir Navab
Reproducibly achieving proper implant alignment is a critical step in total hip arthroplasty (THA) procedures that has been shown to substantially affect patient outcome.
Then, annotations on the 2D X-ray images can be rendered as virtual objects in 3D providing surgical guidance.