Abstract: This paper proposes strategies in level crossing (LC) sampling and reconstruction that provide alias-free high-fidelity signal reconstruction for speech signals without exponentially increasing sample number with increasing bit-depth. We introduce methods in LC sampling that reduce the sampling rate close to the Nyquist frequency even for large bit-depth. The results indicate that larger variation in the sampling intervals leads to alias-free sampling scheme; this is achieved by either reducing the bit-depth or adding a jitter to the system for high bit-depths. In conjunction with windowing, the signal is reconstructed from the LC samples using an efficient Toeplitz reconstruction algorithm.
Abstract: Quantitative measurement of myocardium perfusion is possible with single photon emission computed tomography (SPECT) using a semiconductor detector. However, accumulation of 99mTc-tetrofosmin in the liver may make it difficult to assess that accurately in the inferior myocardium. Our idea is to reduce the high accumulation in the liver by using dynamic SPECT imaging and a technique called time subtraction. We evaluated the performance of a new SPECT system with a cadmium-zinc-telluride solid-state semi- conductor detector (Discovery NM 530c; GE Healthcare). Our system acquired list-mode raw data over 10 minutes for a typical patient. From the data, ten SPECT images were reconstructed, one for every minute of acquired data. Reconstruction with the semiconductor detector was based on an implementation of a 3-D iterative Bayesian reconstruction algorithm. We studied 20 patients with coronary artery disease (mean age 75.4 ± 12.1 years; range 42-86; 16 males and 4 females). In each subject, 259 MBq of 99mTc-tetrofosmin was injected intravenously. We performed both a phantom and a clinical study using dynamic SPECT. An approximation to a liver-only image is obtained by reconstructing an image from the early projections during which time the liver accumulation dominates (0.5~2.5 minutes SPECT image-5~10 minutes SPECT image). The extracted liver-only image is then subtracted from a later SPECT image that shows both the liver and the myocardial uptake (5~10 minutes SPECT image-liver-only image). The time subtraction of liver was possible in both a phantom and the clinical study. The visualization of the inferior myocardium was improved. In past reports, higher accumulation in the myocardium due to the overlap of the liver is un-diagnosable. Using our time subtraction method, the image quality of the 99mTc-tetorofosmin myocardial SPECT image is considerably improved.
Abstract: Diffuse Optical Tomography (DOT) is a non-invasive imaging modality used in clinical diagnosis for earlier detection of carcinoma cells in brain tissue. It is a form of optical tomography which produces gives the reconstructed image of a human soft tissue with by using near-infra-red light. It comprises of two steps called forward model and inverse model. The forward model provides the light propagation in a biological medium. The inverse model uses the scattered light to collect the optical parameters of human tissue. DOT suffers from severe ill-posedness due to its incomplete measurement data. So the accurate analysis of this modality is very complicated. To overcome this problem, optical properties of the soft tissue such as absorption coefficient, scattering coefficient, optical flux are processed by the standard regularization technique called Levenberg - Marquardt regularization. The reconstruction algorithms such as Split Bregman and Gradient projection for sparse reconstruction (GPSR) methods are used to reconstruct the image of a human soft tissue for tumour detection. Among these algorithms, Split Bregman method provides better performance than GPSR algorithm. The parameters such as signal to noise ratio (SNR), contrast to noise ratio (CNR), relative error (RE) and CPU time for reconstructing images are analyzed to get a better performance.
Abstract: The photoacoustic images are obtained from a custom developed linear array photoacoustic tomography system. The biological specimens are imitated by conducting phantom tests in order to retrieve a fully functional photoacoustic image. The acquired image undergoes the active region based contour filtering to remove the noise and accurately segment the object area for further processing. The universal back projection method is used as the image reconstruction algorithm. The active contour filtering is analyzed by evaluating the signal to noise ratio and comparing it with the other filtering methods.
Abstract: An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray’s Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray’s Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data.
Abstract: Electric impedance imaging is a method of
reconstructing spatial distribution of electrical conductivity inside a
subject. In this paper, a new method of electrical impedance imaging
using eddy current is proposed. The eddy current distribution in the
body depends on the conductivity distribution and the magnetic field
pattern. By changing the position of magnetic core, a set of voltage
differences is measured with a pair of electrodes. This set of voltage
differences is used in image reconstruction of conductivity
distribution. The least square error minimization method is used as a
reconstruction algorithm. The back projection algorithm is used to
get two dimensional images. Based on this principle, a measurement
system is developed and some model experiments were performed
with a saline filled phantom. The shape of each model in the
reconstructed image is similar to the corresponding model,
respectively. From the results of these experiments, it is confirmed
that the proposed method is applicable in the realization of electrical
imaging.
Abstract: An alternative approach to the use of Discrete Fourier
Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction
is the use of parametric modeling technique. This method
is suitable for problems in which the image can be modeled by
explicit known source functions with a few adjustable parameters.
Despite the success reported in the use of modeling technique as an
alternative MRI reconstruction technique, two important problems
constitutes challenges to the applicability of this method, these are
estimation of Model order and model coefficient determination. In
this paper, five of the suggested method of evaluating the model
order have been evaluated, these are: The Final Prediction Error
(FPE), Akaike Information Criterion (AIC), Residual Variance (RV),
Minimum Description Length (MDL) and Hannan and Quinn (HNQ)
criterion. These criteria were evaluated on MRI data sets based on the
method of Transient Error Reconstruction Algorithm (TERA). The
result for each criterion is compared to result obtained by the use of a
fixed order technique and three measures of similarity were evaluated.
Result obtained shows that the use of MDL gives the highest measure
of similarity to that use by a fixed order technique.
Abstract: Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.
Abstract: During the last years, the genomes of more and more
species have been sequenced, providing data for phylogenetic recon-
struction based on genome rearrangement measures. A main task in
all phylogenetic reconstruction algorithms is to solve the median of
three problem. Although this problem is NP-hard even for the sim-
plest distance measures, there are exact algorithms for the breakpoint
median and the reversal median that are fast enough for practical use.
In this paper, this approach is extended to the transposition median as
well as to the weighted reversal and transposition median. Although
there is no exact polynomial algorithm known even for the pairwise
distances, we will show that it is in most cases possible to solve
these problems exactly within reasonable time by using a branch and
bound algorithm.
Abstract: Three-dimensional reconstruction of small objects has
been one of the most challenging problems over the last decade.
Computer graphics researchers and photography professionals have
been working on improving 3D reconstruction algorithms to fit the
high demands of various real life applications. Medical sciences,
animation industry, virtual reality, pattern recognition, tourism
industry, and reverse engineering are common fields where 3D
reconstruction of objects plays a vital role. Both lack of accuracy and
high computational cost are the major challenges facing successful
3D reconstruction. Fringe projection has emerged as a promising 3D
reconstruction direction that combines low computational cost to both
high precision and high resolution. It employs digital projection,
structured light systems and phase analysis on fringed pictures.
Research studies have shown that the system has acceptable
performance, and moreover it is insensitive to ambient light.
This paper presents an overview of fringe projection approaches. It
also presents an experimental study and implementation of a simple
fringe projection system. We tested our system using two objects
with different materials and levels of details. Experimental results
have shown that, while our system is simple, it produces acceptable
results.
Abstract: In this paper, we present an analytical analysis of the
representation of images as the magnitudes of their transform with
the discrete wavelets. Such a representation plays as a model for
complex cells in the early stage of visual processing and of high
technical usefulness for image understanding, because it makes the
representation insensitive to small local shifts. We found that if the
signals are band limited and of zero mean, then reconstruction from
the magnitudes is unique up to the sign for almost all signals. We
also present an iterative reconstruction algorithm which yields very
good reconstruction up to the sign minor numerical errors in the very
low frequencies.
Abstract: In this paper we present a generic approach for the problem of the blind estimation of the parameters of linear and convolutional error correcting codes. In a non-cooperative context, an adversary has only access to the noised transmission he has intercepted. The intercepter has no knowledge about the parameters used by the legal users. So, before having acess to the information he has first to blindly estimate the parameters of the error correcting code of the communication. The presented approach has the main advantage that the problem of reconstruction of such codes can be expressed in a very simple way. This allows us to evaluate theorical bounds on the complexity of the reconstruction process but also bounds on the estimation rate. We show that some classical reconstruction techniques are optimal and also explain why some of them have theorical complexities greater than these experimentally observed.