Geometry modeling and nonlinear reconstruction for X-ray guided breast DOT PowerPoint PPT Presentation

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Title: Geometry modeling and nonlinear reconstruction for X-ray guided breast DOT


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Geometry modeling and nonlinear reconstruction
for X-ray guided breast DOT
  • Qianqian Fang, David Boas, Greg Boverman, Quan
    Zhang, Tina Kauffman
  • Massachusetts General Hospital
  • Northeastern University

NTROI
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Outline
  • Instrument overview
  • Binary function based mesh generator
  • Iterative block solver
  • Reconstruction results
  • Summary

3
Why combine X-ray with DOT?
  • Mammography is low-cost and routinely used across
    the country
  • X-ray only provide morphological info.
  • DOT can provide functional measurement but is
    low-resolution.
  • Combined X-ray/DOT imaging can help doctors
    assessment by overlaying functional image on top
    of structural image.

4
System Picture
TOBI tomographical optical breast imaging system
Tomosynthesis 3D Mammography
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Binary function based mesh generation
  • Why another mesh generator?
  • Conventional method for mesh generation from
    medical images
  • segmentation and boundary extraction
  • surface smoothing
  • advance-front method
  • mesh optimization
  • What the new generator can offer?
  • anyone can understand and implement
  • no need for boundary extraction and smoothing
  • high quality elements, no need for mesh
    optimization
  • in some cases, may faster than conventional method

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Prologue Distance function based mesh generation
  • Persson Strang (MIT), 2004 SIAM Review Simple
    mesh generation based on signed-distance
    functions
  • Pros
  • simple
  • high quality
  • Cons
  • difficult for compli-cated geometries
  • slow

http//www-math.mit.edu/persson/mesh/
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Binary Functions
  • A binary function inside or out side

1
-2
2
int binary_shape(double x, double y) return
(xgt2. xlt-2. ygt2. ylt-2.
xxyygt1.)
For medical images, only memory access is
needed, no arithmetic !
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Step 1-3 of 5
  • Step 1 initial mesh
  • Truncating isotropic mesh by binary function
  • Step 2 boundary layer
  • Use Laplacian operator to find out the boundary
    layer
  • Reduce computationalcomplexity fromO(N) to
    O(N1/2) for2D, O(N) to O(N2/3)for 3D
  • Step 3 moving mesh
  • treat mesh as truss system, solve for physical
    equilibrium

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Step 4 of 5 Boundary Correction
  • if nodes move outside the geometry
  • bi-sect search betweenPi and Pi1
  • line search over a circle,find out the closest
    boundary point

Step 5 of 5 Re-Triangulation
  • Moving mesh will change mesh topology, without
    timely updating neighbor list, this may cause
    method to diverge.
  • Delaunay based triangulation (for example QHull)
    can be used (only apply to the nodes within
    boundary layer)

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More complicated cases
  • Mesh generation in 3D or in Rn space
  • Step 1 using uniform grid as initial mesh
  • Step 4 the second line search in boundary
    correction is performed on a (hyper-)sphere
    surface
  • For medical images segmentations
  • Anisotropic elements
  • Non-uniform mesh density
  • Quadtree or Octree

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Examples
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Iterative Block Solver for FEM forward modeling
  • Solving FEM forward equation large scale,
    sparse, complex (or real) entries
  • Direct methods SuperLU, UMFPACK, WSMP
  • Iterative methods CG, BiCG, GMRES, QMR
  • QMR multi-RHS solver(BoyesSeidl,1996)
    Ax1,x2,x3,..,xNb1,b2,b3,,bN
    N block size

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Solver Performance
  • mesh 42122 nodes and 230745 elements
  • RF diffusion equation

optimal block size
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Results Simulations
  • TOMO Slices ForwardRecon meshes

Slice35
Slice50
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Simulation Contd
  • True absorption Recovered absorption
    w/o geometry modeling

A tumor
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Summary
  • Take home messages
  • TOBI RFCWMUX, can co-register with 2D or 3D
    mammography
  • Mesh generator is simple and easy to implement,
    good for mesh generation from medical images
  • Block solver is efficient in solving forward
    problems
  • Problems mesh generator not entirely stable
    some elements close to boundary are not perfect
    3D triangulation produces empty elements.

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Acknowledgements
  • Funding Agencies
  • NIH
  • NTROI
  • Avon Breast Cancer Center
  • Daniel Kopans
  • Richard Moore
  • Dianne Georgian-Smith
  • Jennifer Curry
  • Dianne Scourletis
  • Donna Burgess
  • Jayne Cormier
  • Lockheed Palo Alto Research Laboratories
  • William Boyse
  • Photon Migration Lab at MGH
  • Maria Franceschini
  • Stefan Carp
  • Juliette Selb
  • Elizabeth Hillman
  • Sol Diamond
  • Phill Jones
  • Danny Joseph
  • Ted Hupper
  • Anand Kumar
  • GW Krauss
  • George Themelis
  • ...

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  • Questions?
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