detection of anatomical landmarks
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Georgetown University Medical Center Friday October 6, 2006. Detection of Anatomical Landmarks. Bruno Jedynak Camille Izard. Anatomical Landmarks. Manually defined points in the anatomy ( geometric landmarks) !! Landmarker consistency, variability between exerts - PowerPoint PPT PresentationTRANSCRIPT
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