We present a new data-driven technique for non-invasive electronic imaging of cardiovascular tissues using routinely-measured body-surface electrocardiogram (ECG) signals. While traditional ECG imaging and 3D reconstruction algorithms typically rely on a combination of linear Fourier theory, geometric and parametric modeling, and invasive measurements via catheters, we show in this work that it is possible to learn the complicated inverse map, from body-surface potentials to epicardial or endocardial potentials, by exploiting the powerful approximation properties of neural networks. The key contribution here is a formulation of the inverse problem that allows historical data to be leveraged as ground-truth for training the inverse operator. We provide some initial experiments, and outline a path for extending this technique for real-time diagnostic applications.
Radar based detection of human targets behind walls or in dense urban environments is an important technical challenge with many practical applications in security, defense, and disaster recovery. Radar reflections from a human can be orders of magnitude weaker than those from objects encountered in urban settings such as walls, cars, or possibly rubble after a disaster. Furthermore, these objects can act as secondary reflectors and produce multipath returns from a person. To mitigate these issues, processing of radar return data needs to be optimized for recognizing human motion features such as walking, running, or breathing. This paper presents a theoretical analysis on the modulation effects human motion has on the radar waveform and how high levels of multipath can distort these motion effects. From this analysis, an algorithm is designed and optimized for tracking human motion in heavily clutter environments. The tracking results will be used as the fundamental detection/classification tool to discriminate human targets from others by identifying human motion traits such as predictable walking patterns and periodicity in breathing rates. The theoretical formulations will be tested against simulation and measured data collected using a low power, portable see-through-the-wall radar system that could be practically deployed in real-world scenarios. Lastly, the performance of the algorithm is evaluated in a series of experiments where both a single person and multiple people are moving in an indoor, cluttered environment.
This paper concerns the compensation of specular highlight for handheld image projectors. By employing a projector-camera configuration, where the camera is aligned with the viewer, the distortion caused by nonideal (e.g., colored, reflective) projection surfaces can be estimated from the captured image and compensated for accordingly to improve the projection quality. This works fine when the viewing direction relative to the system is fixed. However, the compensation becomes inaccurate when this condition changes, because the position of the specular highlight changes as well. We propose a novel method that, without moving the camera, can estimate the specular highlight seen from any position and integrate it with Grossberg’s radiometric compensation framework to demonstrate how view-dependent compensation can be achieved. Extensive results, both objective and subjective, are provided to demonstrate the performance of the proposed algorithm.
This paper describes the method of using the finite-element analysis software, PZFlex, to direct the
design of a novel ultrasound imaging system which uses conformal transducer arrays. Current
challenges in ultrasound array technology, including 2D array processing, have motivated exploration
into new data acquisition and reconstruction techniques. Ultimately, these efforts encourage a broader
examination of the processes used to effectively validate new array configurations and image formation
procedures. Commercial software available today is capable of efficiently and accurately modeling
detailed operational aspects of customized arrays. Combining quality simulated data with prototyped
reconstruction techniques presents a valuable tool for testing novel schemes before committing more
costly resources. To investigate this practice, we modeled three 1D ultrasound arrays operating multistatically instead of by the conventional phased-array approach. They are: a simple linear array, a half-circle array with 180-degree coverage, and a full circular array for inward imaging. We present the process used to create unique array models in PZFlex, simulate operation and obtain data, and subsequently generate images by inputting data into a reconstruction algorithm in MATLAB. Further discussion describes the tested reconstruction algorithm and includes resulting images.
KEYWORDS: Ranging, Ultrasonography, Transducers, Acoustics, Signal to noise ratio, Signal processing, Signal detection, Fourier transforms, Signal attenuation, Receivers
This paper presents a method setup for high-frequency ultrasound ranging based on stepped frequency-modulated
continuous waves (FMCW), potentially capable of producing a higher signal-to-noise ratio (SNR) compared to
traditional pulse-echo signaling. In current ultrasound systems, the use of higher frequencies (10-20 MHz) to
enhance resolution lowers signal quality due to frequency-dependent attenuation. The proposed ultrasound
signaling format, step-FMCW, is well-known in the radar community, and features lower peak power, wider
dynamic range, lower noise figure and simpler electronics in comparison to pulse-echo systems.
In pulse-echo ultrasound ranging, distances are calculated using the transmit times between a pulse and its
subsequent echoes. In step-FMCW ultrasonic ranging, the phase and magnitude differences at stepped frequencies are used to sample the frequency domain. Thus, by taking the inverse Fourier transform, a comprehensive range profile is recovered that has increased immunity to noise over conventional ranging methods. Step-FMCW and pulse-echo waveforms were created using custom-built hardware consisting of an arbitrary waveform generator and dual-channel super heterodyne receiver, providing high SNR and in turn, accuracy in detection.
This paper presents the use and evaluation of stepped frequency modulated continuous waves (FMCW) in a conformal
ultrasound array-based medical imaging system currently in development. Conventional medical ultrasound systems
featuring rigid transducer arrays are highly user-dependent and require manual rotation and translation to identify and
image landmarks. Conformal ultrasound arrays have a larger aperture that can follow the surface curvature of the body,
thereby enabling increased data capture without mechanical scanning. The complexity of image reconstruction in
conformal ultrasound necessitates the use of step-FMCW, since it directly captures the frequency space thereby enabling
image reconstruction techniques to operate directly on the data, greatly simplifying and allowing for real-time
performance. Further, FMCW is advantageous in general since it requires lower peak power and produces better
receiver noise characteristics than conventional pulse-echo signaling.
In the proposed stepped FMCW signaling, packets of acoustic waves at stepped frequencies are emitted from transducers
sequentially. Phase and magnitude information from each transmitter-receiver pair of the array are captured producing
the frequency space representation of the conventional A-scan data.
The results comprise of simulations and bistatic experimental data produced by the step-FMCW signaling method, and
obtained using a multistatic transducer array with a stationary metal target. In experimental verification using, the step-
FMCW signaling and processing method gave accurate target detection, thereby demonstrating its viability in a
conformal ultrasound array and imaging system.
A reflective terahertz (THz) system has been under development for imaging and monitoring of skin hydration, and
through consideration of attenuation, scattering, spatial resolution and measurement of sensitivity, the frequency band
0.4 - 0.7 THz has been determined optimal for operation. THz, typically defined as the frequency range between 0.1-10
THz, has been proposed for skin hydration imaging and monitoring primarily due to being non-ionizing radiation and
highly sensitivity to water concentrations. While it is important to maximize measurement sensitivity to changes in water
concentration, the optimal operational frequency band must simultaneously minimize the scattering from the targets (i.e.
skin) and attenuation, as well as maximize the spatial resolution. In terms of atmospheric attenuation, from 0.4 to 1 THz,
there are broad absorption lines at 556 GHz and 750 GHz, and large transmission windows centered at 500, 650, and 870
GHz. Scattering of the energy reflected from skin was show, using modeling, that as the frequency increased there was a
considerable decrease in the power fraction reflected in the specular direction. For measurement sensitivity, it was
shown that a change in reflectivity per change in water volume at 100 GHz was nearly an order of magnitude higher at 1
THz. Finally, as should be expected, higher frequencies were better for spatial resolution. In consideration of the above
criteria, the motivation for using the 0.4-0.7 THz band will be presented as well as an overview the developed THz pulse
reflective imaging system for imaging of skin hydration.
Due to their increased angular coverage around body surfaces, conformal ultrasound transducers may potentially provide
increased signal acquisition relative to rigid medical ultrasound probes and eliminate the need for mechanical scanning.
This paper describes a novel, high efficiency, and robust conformal ultrasound transducer array based on a flexible
substrate of silicon islands joined together using polyimide joints. The array incorporated diced bulk lead zirconate
titanate (PZT) mounted atop the silicon islands as its piezoelectric material for its desirable electromechanical coupling
factor and high piezoelectric coefficients. Parylene thin films deposited over the array reinforced the bendable joints,
encapsulated the metal film interconnects, and formed, in conjunction with the silicon, an acoustical match between the
PZT and soft tissue. Eight element linear arrays were fabricated with a pitch of 3.5 mm, operating at a center frequency
of 12 MHz with a 6dB bandwidth of 27%. The robustness of the transducer was demonstrated by iterative bending
around a 1 cm diameter cylinder, and the durability of the electrical traces and the frequency performance was measured
using a vector network analyzer. This paper presents a robust, durable conformal ultrasound array with the versatility to
scale to enable new applications in diagnostic ultrasound imaging.
In this paper, we present the image reconstruction algorithm developed for a conformal ultrasound
array imaging system operating in the step frequency-modulated continuous wave (FMCW) mode. The
image formation procedure is based on a key relationship that establishes the equivalence between
pulse-echo and step FMCW modalities, and thus permits conversion between the data types. Prior step
FMCW simulation work could then be merged with pulse-echo data collected experimentally to achieve
full-scale synthesis between laboratory data and a structured theoretical framework. We describe how
an experimentally acquired pulse-echo waveform was extracted and incorporated into a step FMCW
imaging simulation to increase image accuracy and improve visualization of physical effects. With
knowledge of the transducer element positions in a multistatic configuration, image reconstruction was
achieved by mapping the complex range profiles over to a target region. Included in this paper are
images reconstructed after waveform synthesis, which feature transducer elements uniformly spaced
around a circular aperture imaging several enclosed targets with different bandwidths.
Reflective terahertz (THz) imaging may potentially become a valuable tool in determining skin hydration due to its non-ionizing photon energy, high sensitivity to water concentration and ability to penetrate through clothing. The high absorption coefficient of water in the THz range is responsible for contrast between substances with lesser or higher degrees of water saturation. Water content, as well as collagen fiber arrangement, varies between different layers of skin. This study sought to determine whether the high THz absorption in water could be exploited to distinguish between these layers. Porcine skin specimens were sectioned into samples of increasing thickness, with the undersides corresponding to different layers in skin. The undersides of the samples were scanned using a THz imaging system operating at a center frequency of 0.5 THz with 0.125 THz of noise-equivalent bandwidth at a standoff of 4 cm and a spot size of 13 mm. Collagen solutions of varying hydrations were also prepared and raster scanned with the same system. The reflectivity of the deeper layers of skin was found to be higher than that of the upper layers, indicating that the deeper layers are more hydrated. The collagen solutions with higher hydration also had higher THz reflectivity. These results suggested that THz is able to distinguish between different layers of skin based on water content and the nature of its association with components in skin.
KEYWORDS: 3D modeling, Cameras, 3D image processing, Video, Colon, Solid modeling, Visual process modeling, Motion models, Data modeling, Computing systems
A 3D colon model is an essential component of a computer-aided diagnosis (CAD) system in colonoscopy to
assist surgeons in visualization, and surgical planning and training. This research is thus aimed at developing
the ability to construct a 3D colon model from endoscopic videos (or images). This paper summarizes our ongoing
research in automated model building in colonoscopy. We have developed the mathematical formulations
and algorithms for modeling static, localized 3D anatomic structures within a colon that can be rendered from
multiple novel view points for close scrutiny and precise dimensioning. This ability is useful for the scenario
when a surgeon notices some abnormal tissue growth and wants a close inspection and precise dimensioning. Our
modeling system uses only video images and follows a well-established computer-vision paradigm for image-based
modeling. We extract prominent features from images and establish their correspondences across multiple images
by continuous tracking and discrete matching. We then use these feature correspondences to infer the camera's
movement. The camera motion parameters allow us to rectify images into a standard stereo configuration and
calculate pixel movements (disparity) in these images. The inferred disparity is then used to recover 3D surface
depth. The inferred 3D depth, together with texture information recorded in images, allow us to construct a 3D
model with both structure and appearance information that can be rendered from multiple novel view points.
The objective of this paper is to examine the structure of the image reconstruction algorithm for synthetic-aperture GPR systems operating with pulse-echo and step-FMCW illumination schemes. The main structure of the image formation algorithms is based on the framework of the backward propagation image formation technique. Mathematical modeling, theoretical analysis, and results from full-scale experiments are included.
In this paper, a new Fourier domain reconstruction algorithm is presented which utilizes the information contained in the known region of the spectrum to estimate the frequency samples in the missing-cone area. Unlike conventional two-dimensional extrapolation techniques, this method uses bi-directional extrapolation to maximize the amount of known information in each extrapolation step. By fully utilizing the information of the measured data, the resulting image provides a more accurate estimation of the electron density distribution. The resolution improvement achieved is mainly due to the proper utilization of the available information in the measurements during the image formation process.
This paper presents moment-based algorithms for matching and motion estimation of 3-D point or line sets and application of these algorithms to object tracking over long time sequences. The motion analysis is done by identifying two sets of coordinate directions based on relative position of points (or lines) before and after the motion. Since these coordinate vectors are motion invariant, the relationship between them gives parameters of rigid motion. However, we need to verify that the sets before and after the motion are matched before applying motion estimation algorithm. We propose several measures suitable for matching of 3-D point (and line) sets, test them on simulated data and develop several criteria for determining noise sensitivity of matching and motion estimation algorithms. Finally, we apply the proposed algorithm to the long sequence (24) of real data (moving vehicle) on which 3-D points were determined by stereo matching.
This paper presents a new approach for extracting surface motion parameters from the left ventricle (LV) data. The data are obtained using biplane (stereo) cineangiography and provided by Dr. David Smith [23]. The data set consists of 3-D coordinates of 30 bifurcation points on the surface of LV through several time frames. If an object undergoes rigid motion, the standard motion parameters are the translation vector and rotation matrix. The above parameters are not sufficient to describe the nonrigid motion, of which the LV motion is an example. Hence, we define the local surface stretching as an additional (with global rotation and translation) motion parameter. The process of recovering the stretching factor from the angiography data consists of three steps. At the first step, the surface of LV is reconstructed at each time instant. The reconstruction procedure involves converting data into polar coordinate system. Then the surface is reconstructed by applying the relaxation (iterative averaging) algorithm in polar coordinates. During the second step we calculate Gaussian curvature at each bifurcation point at each time instant. This achieved by least-squares surface fitting in the window around each point of interest. The third step is actual stretching factor recovery, which is based on comparison of Gaussian curvatures before and after the motion. This formula was first suggested in [11]. The final results of the algorithm are the reconstructed LV surface at each time instant together with cumulative stretching curves for each given bifurcation point.
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