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ABSTRACT: present an algorithm for automatic assessment of left ventricular ejection fraction (EF) and absolute volume from gated Thallium-SPECT myocardial perfusion images. The system consists of two independent blocs for segmentation and computation of JtlrtcttlJrt. rr trltr'octUC a novel jor rrttttort computation of EF based on the epi-cardial contour. The a&orithm was validated against manual border tracing from two physicians on derent modalities, and gave consistent linear agreement.' PET manual rs. automatic - avg. r = 0 91. TI-SPECT manual vs. auto - r = O. 79. The new epicardial method was compared to the endocardial method showing the .former improved performance at high noise. Finale, prelimina 99m k and 2fl-SPECf to those ;btain;d from 'planr gated b&od pool imaging (GB) yielding good results.
09/2002;
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ABSTRACT: We introduce a method for initializing the multiwavelet
decomposition algorithm. The initialization procedure is the orthogonal
projection of the input signal into the space defined by the
multiscaling function. The approach will always have a solution, places
no restrictions on the input (except that it be contained within L<sub>2
</sub>), and can be implemented in a fast algorithm. We present the
details of our approach and compare it with another proposed method of
prefiltering
IEEE Transactions on Signal Processing 12/1998; · 2.63 Impact Factor
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ABSTRACT: Shift-orthogonal wavelets are a new type of multiresolution
wavelet bases that are orthogonal with respect to translation (or
shifts) within one level but not with respect to dilations across
scales. We characterize these wavelets and investigate their main
properties by considering two general construction methods. In the first
approach, we start by specifying the analysis and synthesis function
spaces and obtain the corresponding shift-orthogonal basis functions by
suitable orthogonalization. In the second approach, we take the
complementary view and start from the digital filterbank. We present
several illustrative examples, including a hybrid version of the
Battle-Lemarie (1987, 1988) spline wavelets. We also provide filterbank
formulas for the fast wavelet algorithm. A shift-orthogonal wavelet
transform is closely related to an orthogonal transform that uses the
same primary scaling function; both transforms have essentially the same
approximation properties. One experimentally confirmed benefit of
relaxing the interscale orthogonality requirement is that we can design
wavelets that decay faster than their orthogonal counterpart
IEEE Transactions on Signal Processing 08/1998; · 2.63 Impact Factor
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ABSTRACT: Describes an image processing system for the automatic assessment of ejection fraction (EF) from noisy SPECT left ventricular myocardial perfusion images. A segmentation scheme consisting of an elliptical coordinate transformation, matched filtering and dynamic contour tracking detects the endo- and epicardial boundaries. Computation of EF is performed based on the epi- rather than the endocardial boundary, which proves to be more robust for images with low signal-to-noise ratios. The computation incorporates anatomical constraints of constant myocardial mass and smooth cardiac variation. The algorithm was tested on different image modalities and shows good linear agreement with EFs obtained from conventional approaches based on planar gated blood pool imaging (PET: y=8.7+1.07x, r=0.84, Technetium-99m MIBI SPECT: y=5.0+0.80x, r=0.90, Thallium-201 SPECT: y=23.5+0.82x, r=0.77, RMS error=10.0). The proposed scheme may be an alternative for EF computation without the need for additional image acquisitions
Image Processing, 1997. Proceedings., International Conference on; 11/1997
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ABSTRACT: The authors present an algorithm for automatic assessment of left
ventricular ejection fraction (EF) and absolute volume from gated
Thallium-SPECT myocardial perfusion images. The system consists of two
independent blocs for segmentation and computation of function. The
authors introduce a novel formulation for computation of EF based on the
epi-cardial contour. The algorithm was validated against manual border
tracing from two physicians on different modalities, and gave consistent
linear agreement. PET manual vs. Automatic-avg. r=0.91, Tl-SPECT manual
vs. auto-r=0.79. The new epicardial method was compared to performance
at. High noise. Finally, preliminary comparison were made of EFs
computed for PET, <sup>99m</sup>Tc-SPECT and <sup>201</sup>Tl-SPECT to
those obtained from planar gated blood pool imaging (GBP) yielding good
results. The proposed scheme is specifically designed for
<sup>201</sup>Tl-SPECT, but may be used on other image modalities as
well. It permits EF computation on relatively noisy images without the
need for additional image acquisitions
Computers in Cardiology 1997; 10/1997
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ABSTRACT: We introduce a new method for initializing the multi-wavelet
decomposition algorithm. The approach assumes that the input signal is
contained within some well-defined subspace of L<sub>2</sub> (e.g. space
of bandlimited functions). The initialization algorithm is the
orthogonal projection of the input signal into the space defined by the
multi-scaling function. Unlike an interpolation approach, the projection
method will always have a solution. We provide examples and
implementation details
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on; 05/1997 · 4.63 Impact Factor
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IEEE Signal Processing Letters 06/1996; · 1.39 Impact Factor
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ABSTRACT: We present an overview of the various uses of the wavelet
transform (WT) in medicine and biology. We start by describing the
wavelet properties that are the most important for biomedical
applications. In particular we provide an interpretation of the the
continuous wavelet transform (CWT) as a prewhitening multiscale matched
filter. We also briefly indicate the analogy between the WT and some of
the the biological processing that occurs in the early components of the
auditory and visual system. We then review the uses of the WT for the
analysis of 1-D physiological signals obtained by phonocardiography,
electrocardiography (ECG), mid electroencephalography (EEG), including
evoked response potentials. Next, we provide a survey of wavelet
developments in medical imaging. These include biomedical image
processing algorithms (e.g., noise reduction, image enhancement, and
detection of microcalcifications in mammograms), image reconstruction
and acquisition schemes (tomography, and magnetic resonance imaging
(MRI)), and multiresolution methods for the registration and statistical
analysis of functional images of the brain (positron emission tomography
(PET) and functional MRI (fMRI)). In each case, we provide the reader
with same general background information and a brief explanation of how
the methods work
Proceedings of the IEEE 05/1996; · 6.81 Impact Factor
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ABSTRACT: We present examples of a new type of wavelet basis functions that are orthogonal across shifts but not across scales. The analysis functions are piecewise linear while the synthesis functions are polynomial splines of degree n (odd). The approximation power of these representations is essentially as good as that of the corresponding Battle-Lemarie orthogonal wavelet transform, with the difference that the present wavelet synthesis filters have a much faster decay. This last property, together with the fact that these transformations are almost orthogonal, may be useful for image coding applications.
IEEE Signal Processing Letters 04/1996; · 1.39 Impact Factor
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ABSTRACT: The notion of a mathematically defined optimally resolving gel concentration for components of a pair of molecular species of any given size was developed by Rodbard et al. (Electrophoresis and Isoelectric Focusing on Polyacrylamide Gel, pp. 28-62, de Gruyter, Berlin, 1974) 21 years ago. The mathematical treatment was incorporated into a computer program (T-OPT) for mainframe computers which upon input of the slope and intercept on the mobility axis of the Ferguson plots of the two components, electrophoresis time and temperature, yielded plots of resolution vs gel concentration. The same algorithms were later incorporated into the program ELPHOFIT for personal computers. Ideality of diffusion spreading and zero initial zone width were assumed along with a Gaussian peak distribution and an equal area for both components. Moreover, these programs failed to respond to the practical question of the migration time (or path) required for the resolution at the optimal gel concentration, although an independent program predicting the course of resolution under the assumption of free diffusion band spreading in gels (DAR-001) had been devised by Rodbard for application in preparative elution-PAGE. The present work advances the technology for predicting resolving conditions by presenting a computer program which allows the user (i) to predict the gel concentration which is optimal for obtaining the desired degree of resolution at any migration time, (ii) to prescribe the minimal degree of resolution between two band distributions one wishes to achieve, and (iii) to predict the migration time (or path) required at the optimal gel concentration for the resolution of the two components. The program is written in MATLAB and can be used by any computer that supports MATLAB language.
Analytical Biochemistry 12/1995; 231(2):432-6. · 3.00 Impact Factor
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ABSTRACT: The purpose of this paper is to derive optimal spline algorithms
for the enlargement or reduction of digital images by arbitrary
(noninteger) scaling factors. In our formulation, the original and
rescaled signals are each represented by an interpolating polynomial
spline of degree n with step size one and Δ, respectively. The
change of scale is achieved by determining the spline with step size
Δ that provides the closest approximation of the original signal
in the L<sub>2</sub>-norm. We show that this approximation can be
computed in three steps: (i) a digital prefilter that provides the
B-spline coefficients of the input signal, (ii) a resampling using an
expansion formula with a modified sampling kernel that depends
explicitly on Δ, and (iii) a digital postfilter that maps the
result back into the signal domain. We provide explicit formulas for
n=0, 1, and 3 and propose solutions for the efficient implementation of
these algorithms. We consider image processing examples and show that
the present method compares favorably with standard interpolation
techniques. Finally, we discuss some properties of this approach and its
connection with the classical technique of bandlimiting a signal, which
provides the asymptotic limit of our algorithm as the order of the
spline tends to infinity
IEEE Transactions on Image Processing 04/1995; · 3.04 Impact Factor
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ABSTRACT: The commercial automated gel electrophoresis apparatus (HPGE-1000 of LabIntelligence, Menlo Park, CA) allows one to recover the material migrating and visualized as a fluorescent-labeled band by electrophoresis into a collection cup located above the band at a right angle to the orientation of the separation path. The degree of recovery is a function of sample load (peak area), electrophoresis time at constant field strength, the mobility of the material and band width. Neglecting the latter, recovery of several SDS-proteins was measured as a function of the first three parameters. These measurements were used as a data base for a computer program capable of predicting, by interpolation of the experimental values, the time of electrophoresis needed to obtain a specified degree of recovery, or the degree of recovery obtained after a desired time of electrophoresis into the collection cup.
Applied and theoretical electrophoresis: the official journal of the International Electrophoresis Society 02/1995; 5(1):31-4.
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ABSTRACT: Wavelet transforms offer certain advantages over Fourier transform techniques for the analysis of EEG. Recent work has demonstrated the applicability of wavelets for both spike and seizure detection, but the computational demands have been excessive. We compare the quality of feature extraction of continuous wavelet transforms using standard numerical techniques, with more rapid algorithms utilizing both polynomial splines and multiresolution frameworks. We further contrast the difference between filtering with and without the use of surrogate data to model background noise, demonstrate the preservation of feature extraction with critical versus redundant sampling, and perform the analyses with wavelets of different shape. Comparison is made with windowed Fourier transforms, similarly filtered, at different data window lengths. We here report a dramatic reduction in computational time required to perform this analysis, without compromising the accuracy of feature extraction. It now appears technically feasible to filter and decompose EEG using wavelet transforms in real time with ordinary microprocessors.
Electroencephalography and Clinical Neurophysiology 01/1995; 91(6):442-55.
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ABSTRACT: We describe a fast noniterative algorithm for the evaluation of
continuous spline wavelet transforms at any integer scale m. In this
approach, the input signal and the analyzing wavelet are both
represented by polynomial splines. The algorithm uses a combination of
moving sum and zero-padded filters, and its complexity per scale is
O(N), where N is the signal length. The computation is exact, and the
implementation is noniterative across scales. We also present examples
of spline wavelets exhibiting properties that are desirable for either
singularity detection (first and second derivative operators) or
Gabor-like time-frequency signal analysis
IEEE Transactions on Signal Processing 01/1995; · 2.63 Impact Factor
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ABSTRACT: The authors first describe the general class of approximation
spaces generated by translation of a function ψ(x), and provide a
full characterization of their basis functions. They then present a
general sampling theorem for computing the approximation of signals in
these subspaces based on a simple consistency principle. The theory puts
no restrictions on the system input which can be an arbitrary finite
energy signal; bandlimitedness is not required. In contrast to previous
approaches, this formulation allows for an independent specification of
the sampling (analysis) and approximation (synthesis) spaces. In
particular, when both spaces are identical, the theorem provides a
simple procedure for obtaining the least squares approximation of a
signal. They discuss the properties of this new sampling procedure and
present some examples of applications involving bandlimited, and
polynomial spline signal representations. They also define a spectral
coherence function that measures the “similarity” between
the sampling and approximation spaces, and derive a relative performance
bound for the comparison with the least squares solution
IEEE Transactions on Signal Processing 12/1994; · 2.63 Impact Factor
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ABSTRACT: Four dual-isotopic label methods for determining true fractional absorption of dietary calcium were compared in 23 subjects. The ratio of the integrals of oral label in a 24-h pooled urine to intravenous label in the same urine is called alpha 24h and was taken as the standard against which the others were compared. alpha Spot is the ratio of the fraction of oral label to the fraction of intravenous label in a single urine specimen; alpha Lag is the ratio of the level of oral label in blood 4 h after administration to the level of intravenous label in blood 2 h after administration. alpha Dec is obtained by deconvoluting response to the intravenous label from the response to the oral tracer. Results were as follows: alpha 24h = 0.273 +/- 0.124, alpha Dec = 0.300 +/- 0.101 (n = 14), alpha Spot = 0.359 +/- 0.179, and alpha Lag = 0.271 +/- 0.103. The Bland-Altman approach for comparison of methods was used to show that results for alpha Spot and alpha Lag can be expected, with a 95% confidence limit, to differ from the value of alpha 24h by 60 and 69%, respectively. The results for alpha Dec were shown to be not only indistinguishable from alpha 24h but identical from a theoretical perspective.
Journal of Nutrition 06/1994; 124(5):674-82. · 3.92 Impact Factor
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ABSTRACT: The authors are concerned with the derivation of general methods
for the L <sub>2</sub> approximation of signals by polynomial
splines. The main result is that the expansion coefficients of the
approximation are obtained by linear filtering and sampling. The authors
apply those results to construct a L <sub>2</sub> polynomial
spline pyramid that is a parametric multiresolution representation of a
signal. This hierarchical data structure is generated by repeated
application of a REDUCE function (prefilter and down-sampler). A
complementary EXPAND function (up-sampler and post-filter) allows a
finer resolution mapping of any coarser level of the pyramid. Four
equivalent representations of this pyramid are considered, and the
corresponding REDUCE and EXPAND filters are determined explicitly for
polynomial splines of any order n (odd). Some image processing
examples are presented. It is demonstrated that the performance of the
Laplacian pyramid can be improved significantly by using a modified
EXPAND function associated with the dual representation of a cubic
spline pyramid
IEEE Transactions on Pattern Analysis and Machine Intelligence 05/1993; · 4.91 Impact Factor
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ABSTRACT: The use of continuous B-spline representations for signal
processing applications such as interpolation, differentiation,
filtering, noise reduction, and data compressions is considered. The
B-spline coefficients are obtained through a linear transformation,
which unlike other commonly used transforms is space invariant and can
be implemented efficiently by linear filtering. The same property also
applies for the indirect B-spline transform as well as for the
evaluation of approximating representations using smoothing or least
squares splines. The filters associated with these operations are fully
characterized by explicitly evaluating their transfer functions for
B-splines of any order. Applications to differentiation, filtering,
smoothing, and least-squares approximation are examined. The extension
of such operators for higher-dimensional signals such as digital images
is considered
IEEE Transactions on Signal Processing 03/1993; · 2.63 Impact Factor
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ABSTRACT: For pt.I see ibid., vol.41, no.2, p.821-33 (1993). A class of
recursive filtering algorithms for the efficient implementation of
B-spline interpolation and approximation techniques is described. In
terms of simplicity of realization and reduction of computational
complexity, these algorithms compare favorably with conventional matrix
approaches. A filtering interpretation (low-pass filter followed by an
exact polynomial spline interpolator) of smoothing spline and
least-squares approximation methods is proposed. These techniques are
applied to the design of digital filters for cubic spline signal
processing. An efficient implementation of a smoothing spline edge
detector is proposed. It is also shown how to construct a cubic spline
image pyramid that minimizes the loss of information in passage from one
resolution level to the next. In terms of common measures of fidelity,
this data structure appears to be superior to the Gaussian/Laplacian
pyramid
IEEE Transactions on Signal Processing 03/1993; · 2.63 Impact Factor
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IEEE Trans. Pattern Anal. Mach. Intell. 01/1993; 15(4):364-379.
