Proceedings IEEE International Symposium on Biomedical Imaging
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Spectrum analysis of microwave breast examination data and reconstructed images
- Trang 62-65
A broadband microwave tomographic imaging system is being developed for breast
cancer detection which exploits the significant electrical property contrast
between normal and malignant tissue. The improved image reconstruction algorithm
directly processes the log-magnitude and phase values of the measured fields
with the frequency rich data set being utilized to acquire the absolute
scattered phas...
#Image analysis #Image reconstruction #Tomography #Microwave imaging #Breast cancer #Cancer detection #Frequency measurement #Phase measurement #Scattering #Wrapping
Statistically-based reorientation of diffusion tensor field
- Trang 757-760
Presents a new method for warping of diffusion tensor fields. The proper
reorientation of a tensor field requires knowledge of the underlying fiber
orientation, which is not known a priori. Accordingly, a probabilistic
representation of the fiber direction is adopted and used in a Procrustean
estimation of the rotational component of the warping field. The estimated
rotational component, along wit...
#Tensile stress #Anisotropic magnetoresistance #Diffusion tensor imaging #Signal to noise ratio #Eigenvalues and eigenfunctions #Radiology #Biomedical imaging #Resonance #Microscopy #Fuses
The elastic reconstruction of soft tissues
- Trang 1035-1038
A finite element based nonlinear inverse scheme is presented to reconstruct the
elastic properties of soft tissues subjected to an external compression. An
objective function relating the least-square difference of model-predicted and
measured displacement or strain fields from a sequence of images (B-mode or MRI)
is minimized with respect to the unknown material parameters. To obtain
physically m...
#Biological tissues #Image reconstruction #Strain measurement #Finite element methods #Image coding #Displacement measurement #Magnetic resonance imaging #Biological materials #Material properties #Constraint optimization
Rapid semi-automated segmentation and analysis of neuronal morphology and function from confocal image data
- Trang 233-236
Confocal microscopy combined with cellular labeling techniques can be an
effective method for imaging the morphology of a cell as well as various
functional characteristics in vivo. Current analysis methods are manual, and
therefore, time-consuming and prone to error. Through the development of custom
algorithms and application design, the analysis process can be improved to
decrease analysis time...
#Image segmentation #Image analysis #Morphology #Algorithm design and analysis #Reproducibility of results #Application software #Microscopy #Labeling #In vivo #Process design
Optical Doppler coherence tomography algorithms: quantitative analysis
- Trang 293-296
We present, to our knowledge, the first quantitative comparisons of five flow
estimation algorithms for optical Doppler coherent tomography. We have used
simulated 1D, 2D, and in vivo blood flow data to investigate the estimation
accuracy and sensitivity of these algorithms. We introduce, among these five
methods, 3 new algorithms: weighted centroid, sliding-window filtering, and
autocorrelation. ...
#Tomography #Algorithm design and analysis #Optical filters #Optical sensors #Filtering algorithms #Autocorrelation #Image motion analysis #In vivo #Blood flow #Adaptive filters
A shape reconstruction method for diffuse optical tomography using a transport model and level sets
- Trang 1015-1018
A two-step shape reconstruction method for diffuse optical tomography (DOT) is
presented which uses adjoint fields and level sets. The propagation of
near-infrared photons in tissue is modeled by the time-dependent linear
transport equation, of which the absorption parameter has to be reconstructed
from boundary measurements. In the shape reconstruction approach, it is assumed
that the inhomogeneo...
#Shape #Reconstruction algorithms #Tomography #Level set #Nonlinear optics #Absorption #US Department of Transportation #Optical propagation #Equations #Inverse problems
A new convergent MAP reconstruction algorithm for emission tomography using ordered subsets and separable surrogates
- Trang 409-412
We investigate a new, fast and provably convergent MAP reconstruction algorithm
for emission tomography. The new algorithm, termed C-OSEM has its origin in the
alternating algorithm derivation of the well known EM algorithm for emission
tomography. In this re-derivation, the complete data explicitly enters the
objective function as an unknown variable. While the entire complete data gets
updated i...
#Reconstruction algorithms #Tomography #Image reconstruction #Smoothing methods #Bayesian methods #Cost function #Biomedical imaging #Radiology #Physics #Data models
3D reconstruction of 2D crystals from projections in real space
- Trang 689-692
A new algorithm for 3D reconstruction of two-dimensional crystals from
projections is presented, and applied to biological macromolecules imaged using
electron microscopy. Its main departure from the traditional approach is that it
works in real space, rather than in Fourier space, and is iterative. This
approach has the advantage of making it convenient to introduce additional
constraints (such a...
#Crystals #Image reconstruction #Transmission electron microscopy #Crystallization #Lattices #Iterative methods #Electron microscopy #Fourier transforms #Iterative algorithms #Molecular biophysics
Multiscale tumor detection and segmentation in mammograms
- Trang 213-216
Breast cancer is a leading cause of death among women. Automatic computer-aided
analysis method can help radiologists to make more reliable and efficient
decisions. Tumors and other abnormalities are of basic interests that need to be
segmented and extracted in mammograms. In this paper, a new wavelet-packet
multiscale image segmentation method is presented first. By combining this new
method with...
#Tumors #Image segmentation #Wavelet packets #Gray-scale #Breast cancer #Spatial resolution #Breast neoplasms #Computer aided analysis #Discrete wavelet transforms #Reliability engineering
Support vector machine learning for detection of microcalcifications in mammograms
- Trang 201-204
Microcalcification (MC) clusters in mammograms can be an indicator of breast
cancer. In this work we propose for the first time the use of support vector
machine (SVM) learning for automated detection of MCs in digitized mammograms.
In the proposed framework, MC detection is formulated as a supervised-learning
problem and the method of SVM is employed to develop the detection algorithm.
The propos...
#Support vector machines #Machine learning #Support vector machine classification #Breast cancer #Risk management #Radiology #Detection algorithms #Databases #Calcium #Breast tissue