Detection of Anatomical Landmarks Bruno Jedynak Camille Izard Georgetown University Medical Center Friday October 6, 2006
Jan 19, 2016
Detection of Anatomical Landmarks
Bruno Jedynak
Camille Izard
Georgetown University Medical CenterFriday October 6, 2006
Anatomical Landmarks
• Manually defined points in the anatomy ( geometric landmarks)
• !! Landmarker consistency, variability between exerts
• Used as is to analyze shapes• Used as control point for image
segmentation/registration
Automatic landmarking
• Given: a set of manually landmarked images
• Goal: build a system that can landmark new images
• The system must adapt to different kind, different number of landmarks
Automatic landmarking Example:
• Given: 38 images expertly landmarked. K landmarks per image
• Goal: landmark new images• Mean error per new image
Or expert evaluation
Template matching paradigm
Identify landmarks with a deformation of the 3d space.
Examples of deformations:
Affine
Splines
Diffeomorphisms
Forward model
Brain MRI gray-values are modeled as a mixture of Gaussians distributions.
There are 6 components in the mixture: CSF,GM, WM, CSF-GM, GM-WM, VeryWhite (Skull, blood vessels, …)
Estimating the tissue probability map
• Learn the photometry of each image
• Register each image on the template
• Use the E.M. algo. for mixture of Gaussians to estimate
Automatic landmarking of a new image
• Learn the photometry parameters
• Use gradient ascent to maximize