3d fib-sem image segmentation and advanced …efug.imec.be/efug2012_14_lichau.pdf3d fib-sem image...
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Data: U Alberta Data: U Alberta
Data: NIST
3D FIB-SEM Image Segmentation
and Advanced Characterization
EFUG Meeting 2012 October 1st - Cagliari, Italy
Outline
About VSG
3D imaging from visualization to characterization
FIB/SEM reconstruction
Image processing and segmentation for characterization
Registration and data fusion
Solving Visualization and Analysis challenges since 1986
Open Inventor ®
3D Development Toolkit
• Oil & Gas, Geosciences, Mining
• Medical and Life Sciences
• Engineering and Simulation
Amira ®
3D Visualization Software
• Life Sciences
• Biomedical Research
• Pharmaceutical Industry
Avizo ®
3D Analysis Software
• Materials and Geoscience
• Industrial Inspection
• Engineering & Simulation
Visilog 2D Image Processing
• Biology
• Pharmaceutical
• Materials Research
On August 1, 2012,
FEI acquired VSG
and
Widely used in Materials Research, Industrial Inspection, Geoscience, Life Sciences
Any material, any size, any scale, any imaging modality
Research, prototyping, and industrial applications
The power of FIB-SEM 3D Imaging
Application areas Geosciences Reservoir rocks, CO2 sequestration Life sciences Tissue Material sciences Fuel cells Catalysts Ceramics Polycrystalline Metals
Semiconductors Failure analysis
Defect inspection in nanowires
Nanyang Technological University, Singapore
From visualization to characterization
Characterization of delaminations at a chip / molding
compound interface. Courtesy A. Rucki
BGA defect analysis Modeling topology
Intermetallic microstructural analysis in tin-plated copper (tin whiskers)
NIST and VSG Marsh et al. 2010. Microscopy and Microanalysis.
Case Studies: Metals
Global Metrics
Fractal dimension of basal surface: 2.31
Degree of anisotropy of interspersed: 0.598
3D Density of interspersed: 0.13 grain / μm3
Population Metrics [Combinatorial filters]
Volume
Surface Area
Length
Width
Aspect Ratio
Orientation
Etc.
Case Study: Solid Oxide Fuel Cells
Characterizing Porous Materials
• Image-based quantification
• Total porosity, Connected porosity, Included Porosity
• Tortuosity, coordination
• Propagation distance
• Modeling-based quantification with Avizo XLab
• Permeability Tensor and Absolute Permeability
• Molecular Diffusivity
• Formation Factor
• Heat Conductivity (coming soon)
Data generously shared by MNT Lab University of Alberta
Image to Simulation Workflow
Skeletonization
CAE solvers Abaqus, Ansys, Comsol,
Fluent, OpenFoam, StarCCM+, etc.
Pore Network Modeling
Mesh generation
Direct calculation of physical property
Avizo XLab
micro-CT image stack
Avizo Fire
Avizo Fire Avizo Fire
Image Segmentation
Avizo Wind
Avizo Fire
Absolute permeability
Molecular diffusivity
Electrical resistivity
Mesh Generation workflow
Segmentation Reconstruction 3D Grid Generation Export
DXF, STL…
The problem with real-world imaging
Idealized imaging
High resolution Resolve small features
High contrast Differentiate different materials High signal fidelity Uniform response High spatial fidelity Distortion free
The problem with real-world imaging
Idealized imaging
High resolution Resolve small features
High contrast Differentiate different materials High signal fidelity Uniform response High spatial fidelity Distortion free Ideal image
The problem with real-world imaging
Idealized imaging
Noisy image
High resolution Resolve small features
High contrast Differentiate different materials High signal fidelity Noise, Non-uniform illumination High spatial fidelity Distortion free
The problem with real-world imaging
Idealized imaging
High resolution Resolve small features
High contrast Differentiate different materials High signal fidelity Noise, Non-uniform illumination High spatial fidelity Distortion free
The problem with real-world imaging
Idealized imaging
Noisy image
High resolution Resolve small features
High contrast Differentiate different materials High signal fidelity Noise, Non-uniform illumination High spatial fidelity Distortion free
The problem with real-world imaging
Idealized imaging
Noisy image with foreshortening
High resolution Resolve small features
High contrast Differentiate different materials High signal fidelity Noise, Non-uniform illumination High spatial fidelity Foreshortening, shear, Misalignment
Signal fidelity artifacts manifest themselves in the histogram
FIB-SEM Shale
Signal fidelity artifacts manifest themselves in the histogram
FIB-SEM Steel
Unprocessed
Signal fidelity artifacts manifest themselves in the histogram
Data generously shared by Georgs-Marienhutte
FIB-SEM Steel
Shadow corrected
Signal fidelity artifacts manifest themselves in the histogram
Data generously shared by Georgs-Marienhutte
FIB-SEM Steel
“Denoised”
Signal fidelity artifacts manifest themselves in the histogram
Data generously shared by Georgs-Marienhutte
FIB-SEM Imaging artifacts
Artifacts
Geometrical distortions Foreshortening Stack alignment Z-shear
Signal fidelity artifacts Noise Shadowing Curtaining Charging Pore-backs Pore halos
Common workflow to interpreting 3d structure
Common workflow to interpreting 3d structure
Visualization Volume Rendering, Surface, Slice
Image processing Greyscale transforms Geometry transforms Image filters Mathematical morphology Image segmentation
Quantitative Analysis Image to table
Simulation Image to simulation pathway
Generic image formats TIFF, BMP, JPG
Microscopy image formats MRC
Home-grown research formats Raw (sometimes with header)
Light Microscopy PSF Z-drop Non-uniform illumination
TEM Tomography Missing wedge CTF
FIB-SEM Shadowning Mis-alignment Shearing
Artifacts may be technique specific
2D Alignment
2D Alignment Selective alignment by intensities or 3D mask
Shearing correction
Shadowing Trench walls and floor can occlude signal and cause locally darker regions Flatfield correction
Detector noise Curtaining Image Smoothing
Pore backs Pore halos Relief artifacts
FIB-SEM Geometrical
• Alignment • XY displacement • Calibration of slice thickness (Z)
• Foreshortening correction (Y) • Shearing (along Z-direction) • Masking
Shadowing Noise Curtaining
Artifacts may be technique specific
From greyscale to binary First stage of segmentation
Thresholding or other binarization
Refining the binary image Second stage of segmentation
Grain boundary reconstruction
Indexing all binary objects
Connected component labeling
Population measurements
Properties upscaling – shale rock permeability case
Medical CT: 0.4mm
Resolution?
Medical CT: 0.6mm uCT: 0.009mm
Solid (e.g., organic matter)/Fluid (e.g., oil)
Substitution?
Scanning Electron Microscope
Downscale and Upscale
Heterogeneity segmentation
1mm
H1: Pores 7.9%
H2: Organic Matter: 14.6%
H3: Mineral 77.5%
uCT: 25um resolution
FIB-SEM: 20nm resolution
FIB-SEM: 20nm resolution
Pores 4.6% OM: 0% Mineral: 95.4%
Pores 37.7% OM: 58.3% Mineral: 4%
2um
1um
data1
data3
data2
Choosing the ROI
CLSM SEM
CLSM FIB-SEM
Sample: Mung bean root nodule colonized by nitrogen-fixing bacteria
D-A-CH FIB Workshop 2011 Zürich
Correlative microscopy
Tool for manual and automatic slice alignment
Image segmentation and advanced characterization of 3D FIB-SEM Reconstructions
Data: U Alberta Data: U Alberta Data: NIST Data: ExxonMobil
Summary
• Universal workflow applies
• Analysis hinges on segmentation
• Microstructure analysis is easy
• Numerical modeling is getting easier
• Increasing use of data registration and fusion
Catalog of artifacts
• Geometrical artifacts
• Rigid alignment
• Ineleastic alignment
• Shear
• Foreshortening
• Signal fidelity artifacts
• Charging
• Curtaining
• Noise
• Shadowing
• Pore-backs
• Pore halos
Avizo 7.1 coming soon
Enhanced FIB Stack Wizard
Filter Sandbox
Registration and data fusion tutorials
New Animation Producer
XLab new solvers
Molecular Diffusion
Electrical Resisivity
New volume to surface mapping
Surface rendering optimized
Colormap port enhanced
And more
Data: U Alberta Data: U Alberta
Data: NIST
THA NK YOU
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