Transcript Ge Wang, PhD, Director SBES Division & ICTAS Center for Biomedical Imaging VT-WFU School of Biomedical Engineering & Sciences Virginia Tech, Blacksburg, VA,

Ge Wang, PhD, Director
SBES Division & ICTAS Center for Biomedical Imaging
VT-WFU School of Biomedical Engineering & Sciences
Virginia Tech, Blacksburg, VA, USA
[email protected]
October 1, 2010
Source
Interior Tomography (2007)
Beam
Beam
ROI
Object
Object
Regular Reconstruction
Known
Sub-region
Beam
Interior Problem
Sparsity
Model
ROI
Object
Landmark-based
Interior Tomography
Beam
ROI
Object
Sparsity-based
Interior Tomography
First Paper (May 2007)
Independent Work (Oct. 2007)
Interior CT Patent
Literature Analysis
Outline
• Less Is Deeper
• Less Is Larger
• Less Is Faster
• Less Is Less
• Less Is More
Less Is Deeper
Use of less projection data for accurate
image reconstruction demands deeper
insight, more advanced theory and more
powerful tools.
Computed Tomography (Wholesale)
Measurement
y
Sinogram
t

P( , t )

p
x
Object
X-rays
f ( x, y)
Reconstruction
t
Inner Vision with Local Data (Retail)
Measurement
y
Sinogram
t

P( , t )
x
Object
X-rays

f ( x, y)
X X
Reconstruction
t
Earliest BPF Formula (1991)
Half-PI-Line Reconstruction (2006)
Field of View (FOV)
Partial-PI-Line
Extrapolation from a Known Point (2006)
FOV
?
Curved Filtering Path (2003)
?
Interior Reconstruction
Global
FBP
Local
FBP
Local
SART
Interior
Recon
(a)
(b)
(HU)
(HU)
500
500
0
0
-500
-500
(c)
-1000
50
100
150
200
(Pixel)
(d)
-1000
50
100
150
200
(Pixel)
HOT
Sparsity-based Interior Recon
Outline
• Less Is Deeper
• Less Is Larger
• Less Is Faster
• Less Is Less
• Less Is More
Less Is Larger
Acquisition of less projection data is
achieved with a narrower beam, and an
object larger than the beam width is not a
concern.
X-ray
Beam
Rotation Axis
Preclinical Nano-CT
Central
Stop
Sample
Zone
Plate
Condense
Lens
ROI
Sample Stage
Phase Ring
Potential for Study on Earliest Life
Hagadorn JW, et al. (2006) Cellular and subcellular structure of Neoproterozoic embryos.
Science 314:291–294
Big Patient Problem
Outline
• Less Is Deeper
• Less Is Larger
• Less Is Faster
• Less Is Less
• Less Is More
Less Is Faster
Less data means smaller detector size,
faster frame rate, and more imaging chains,
all of which contribute to accelerate the
data acquisition process.
Spiral Cone-beam CT
Dual-source Clinical CT (2005)
Multi-source Interior Tomography
ROI
Wang G, Yu H, Ye YB. Virginia Tech Patent Disclosure on May 15, 2007,
US Patent Application 12/362,979 allowed on October 21, 2009
Ye YB, Yu HY, Wei YC, Wang G. International Journal of Biomedical Imaging, Article ID:63634, 2007
Wang G, Yu H, Ye Y. Medical Physics. 36:3575-3581, 2009
From Scanning to Roaming
Outline
• Less Is Deeper
• Less Is Larger
• Less Is Faster
• Less Is Less
• Less Is More
Less Is Less
Less data is equivalent to less radiation
dose, because of not only a narrower beam
but also a more relaxed angular sampling
requirement in the longitudinal studies or
multi-scale scenarios.
Reduced Angular Sampling Rate
Need 4 Projections
Need 2 Projections
Statistical Interior Tomography
Phantom [0.9 1.1]
ROI
200,000 photons
ITHT
Known sub-Region
Work in progress from Qiong Xu & Xuanqin Mou
(China) in collaboration with Wang G & Yu HY
50,000 photons
Hilbert Region
ML
Outline
• Less Is Deeper
• Less Is Larger
• Less Is Faster
• Less Is Less
• Less Is More
Less Is More
Use of less data is advantageous in more
modalities beyond CT, such as other
straight-ray tomographic techniques and
even in small-angle curvilinear geometry,
and more applications of various types.
Furthermore, less data means more
computational time!
Interior-MRI
……………………………………
Interior-MRI
Traditional MRI
Interior MRI
Zhang J, Yu HY, Corum C, Garwood M, Wang G: Exact and stable
interior ROI reconstruction for radial MRI. SPIE 7258: 2585G, 8 pages,
Feb. 2009, Orlando, FL, USA
Interior Electron Tomography
Ge Wang, Hengyong Yu
Limited Angle Interior Tomography
Interior SPECT
Interior-SPECT
FOV
µa =0.3cm-1
Support
Yu HY, Yang JS, Jiang M, Wang G:
Interior SPECT- Exact and stable ROI
reconstruction from uniformly attenuated
local projections; Communications in
Numerical Methods in Engineering,
25(6):693-710, 2009
Noisy data
Known
µa =0.15cm-1
Ideal data
µa =0cm-1
Practical Implications
Conclusion
• Less Is Deeper
• Less Is Larger
• Less Is Faster
• Less Is Less
• Less Is More
Less Is Not Always Better
Link of Localities
Pictures from http://www.bing.com
Future Work
• Multi-scale Interior Tomography
• Multi-parameter Interior Tomography
• Multi-energy Interior Tomography
SBES Advanced Multi-scale CT Facility
Smaller Scales?
Larger Scales?
Multi-parameter CT
Grating-based Imaging
Dark-field Tomography
Wang G, Cong W, Shen H, Zou Y: Varying Collimation for Dark-Field Extraction.
International Journal of Biomedical Imaging. 2009, Article ID 847537, 2010
Multi-energy CT
Future Work
• Theoretical Extension
• Computational Optimization
• Systematic Evaluation
• Biomedical Applications
• Interdisciplinary Collaboration
Acknowledgment
The results in this presentation are of collaborative nature.
Major collaborators include Drs. Hengyong Yu, Yangbo
Ye, Jiangsheng Yang, Ming Jiang, Steve Wang, Michael
Fesser, Erik Ritman, Deepak Bharkhada, Bruno DeMan,
Guohua Cao, Otto Zhou, Alexander Katsevich, et al. The
work was partially supported by National Institutes of
Health/National Institute of Biomedical Imaging and
Bioengineering Grants EB002667, EB009275, and
EB011785 as well as National Science Foundation
NSF/CMMI 0923297.
Thank You!