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Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science...

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Hierarchical Statistical Hierarchical Statistical Modeling of Boundary Image Modeling of Boundary Image Profiles Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA Supported by NIH-NCI P01 CA47982.
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Page 1: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Hierarchical Statistical Modeling of Hierarchical Statistical Modeling of Boundary Image ProfilesBoundary Image Profiles

Sean Ho

Department of Computer Science

University of North Carolina, Chapel Hill, NC, USA

Supported by NIH-NCI P01 CA47982.

Page 2: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Bayesian image segmentationBayesian image segmentation

Geometric priorGeometric prior Image matchImage match

log p(m | I) = log p(m) + log [p(I | m) / p(I)]log p(m | I) = log p(m) + log [p(I | m) / p(I)]

Page 3: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Model-based segmentationModel-based segmentation

Shape Shape representationrepresentation PDM, SPHARM, M-PDM, SPHARM, M-

rep, level-set, etc.rep, level-set, etc.

Probabilistic Probabilistic modelmodel Likelihood of a given Likelihood of a given

shapeshape

Shape typicality Shape typicality (“prior”)(“prior”)

Image Image representationrepresentation Global (no corresp.)Global (no corresp.) Local (req. corresp.)Local (req. corresp.)

Probabilistic Probabilistic modelmodel Fit of a given shape Fit of a given shape

in a given imagein a given image

Model-to-image Model-to-image matchmatch

Page 4: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Example: corpus callosumExample: corpus callosum

Automatic segmentationAutomatic segmentation Shape rep: 2D Fourier (Staib et al)Shape rep: 2D Fourier (Staib et al) Image rep: 1D profiles normal to Image rep: 1D profiles normal to

boundary (Cootes et al)boundary (Cootes et al) Each profile independent of its neighborsEach profile independent of its neighbors 100 profiles => 100 separate PCAs100 profiles => 100 separate PCAs

((moviemovie))

Page 5: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Some examples of related workSome examples of related work

Snakes: gradient magnitudeSnakes: gradient magnitude Also region-based inside/outside snakesAlso region-based inside/outside snakes

Template matching, correlationTemplate matching, correlation ASM/SPHARM: independent profilesASM/SPHARM: independent profiles AAM: hierarchical over whole imageAAM: hierarchical over whole image

Page 6: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Object-intrinsic coordinatesObject-intrinsic coordinates

Use SPHARM parameterization to sample Use SPHARM parameterization to sample image in collar around object boundaryimage in collar around object boundary

Page 7: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Profiles in normalized coordsProfiles in normalized coords

Along-boundary directionAlong-boundary direction

Acr

oss-

bdy

Page 8: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Across-boundary modelAcross-boundary model

Page 9: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Driving QuestionsDriving Questions

fine sampling necessary?fine sampling necessary? pyramidpyramid object specificobject specific

how do we deal with noise? how do we deal with noise? would like to blur along boundarywould like to blur along boundary

local statistical modellocal statistical model

Page 10: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Along-boundary modelAlong-boundary model

Gaussian profile pyramidGaussian profile pyramid

out in out in

arcl

engt

h

arcl

engt

h

Page 11: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Laplacian profile pyramidLaplacian profile pyramid

--

==

Page 12: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Laplacian, local differencesLaplacian, local differences

uu

Page 13: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Profiles in 3DProfiles in 3D

Use SPHARM parameter space of unit Use SPHARM parameter space of unit spheresphere

Recursive subdivision with icosahedronRecursive subdivision with icosahedron 00thth level: 20 profiles level: 20 profiles 11stst level: 20*4 profiles level: 20*4 profiles

1-way Markov chain1-way Markov chain

Page 14: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Profiles along 1 object in 3DProfiles along 1 object in 3D

Profiles along red meridian line

Inside Outside

Inside

Outside

All profiles

Left Hippocampus

Page 15: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Profiles around 1 hippocampusProfiles around 1 hippocampus

Inside Outside Inside Outside

Page 16: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Profiles: at 1 point on boundaryProfiles: at 1 point on boundary

1 1 corresponding point on population of corresponding point on population of 10 hippocampi10 hippocampi

Step-edge visibleStep-edge visible More variability outsideMore variability outside

case

nu

mb

ers

Page 17: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

At another point on boundaryAt another point on boundary

Large variability across subjectsLarge variability across subjects Mean profile nearly flat: low confidenceMean profile nearly flat: low confidence

case

nu

mb

ers

Page 18: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Current / ongoing workCurrent / ongoing work

SPHARM segmentation framework:SPHARM segmentation framework: Standard ASM-like independent profilesStandard ASM-like independent profiles New hierarchical along-boundary modelNew hierarchical along-boundary model New statistical model (local PCA, MRF)New statistical model (local PCA, MRF)

Testbed in 2D with 71 corpora callosaTestbed in 2D with 71 corpora callosa Testbed in 3D with:Testbed in 3D with:

90 caudates (L/R)90 caudates (L/R) 90 hippocampi (L/R)90 hippocampi (L/R)

Page 19: Hierarchical Statistical Modeling of Boundary Image Profiles Sean Ho Department of Computer Science University of North Carolina, Chapel Hill, NC, USA.

Average of 20Average of 20 multiscale along multiscale along

boundaryboundary Image match model for Image match model for

segmentationsegmentation

Profile PyramidProfile Pyramid


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