614437 Nonrigid brain image registration using a statistical deformation model PowerPoint PPT Presentation

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Title: 614437 Nonrigid brain image registration using a statistical deformation model


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6144-37 Non-rigid brain image registration using
a statistical deformation model
  • Deformation field is modeled as a linear
    combination of the principal models of 64
    deformations.
  • Viscous Fluid Model to create the deformations.
  • 16 images from database and 3 new images.
  • MI is higher using the new algorithm than using
    viscous fluid model.

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6144-38 Nonrigid registration using
regularization that accomodates local tissue
rigidity
  • Ignoring the elasticity differences between
    tissue types can result in non-physical results.
  • A space variant regularization function which
    constrain the local jacobian of the deformation
    is developed.

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6144-218 A whole brain morphometric analysis of
changes associated with pre-term birth
  • The purpose is to identify structural
    differences in preterm infants.
  • 88 preterm infants and 19 term born controls.
  • PCA (Principal Component Analysis) and MLDA
    (Maximum uncertainty Linear Discriminant
    Analysis)

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A good classification result between preterm and
term groups.
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6144-86 Automatic sub-volume registration by
probabilistic random search
  • The purpose is to map one part or one organ to
    the entire atlas data.
  • Most of existing intensity based algorithm
    require the manual pre-registration.
  • Probabilistic random search allows to find the
    optimal transformation without a close
    initialization.

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6144-42 A comparison of FFD-based nonrigid
registration and AAMs applied to myocardial
perfusion MRI
  • FFD vs. AAMs
  • FFD Free-form Deformations
  • AAMs Active Appearance Models
  • FFD provides similar accuracy as the AAMs in
    terms of point to point errors.
  • AAMs provide higher accuracy for point to curve
    error.

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6144-36 Mjolnir deformable image registration
using feature diffusion
  • Mjolnir modification of HAMMER.
  • HAMMER Hierarchical Attribute Matching
    Mechanism for Elastic Registration.
  • There are significant improvements in accuracy
    with reduction in computation time.

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6144-33 Multimodal 2D-3D non-rigid registration
  • X-ray projections 3D CT data
  • Algebraic Reconstruction Technique (ART)
  • Curvature registration

6144-44 Registration of 2D cardiac images to
real-time 3D ultrasound volumes for 3D stress
echocardiography
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6144-04 Oriented active shape models
  • Combine ASM with live wire.

6144-21 Improved 3D live-wire segmentation for 3D
CT chest image analysis
  • Modify the standard 2D live-wire algorithm.
  • Define a new 3D live-wire formulation.

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6144-01 Image segmentation using local shape and
gray-level appearance models
6144-18 Automatic segmentation of vessels in
breast MR as a false positive elimination
technique for lesion detection and segmentation
using the shape tensor
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