W. Clem Karl

Compressed sensing of mono-static and multi-static SAR

In this paper we study the impact of sparse aperture data collection of a SAR sensor on reconstruction quality of a scene of interest. Different mono and multi-static SAR measurement configurations produce different Fourier sampling patterns. These patterns reflect different spectral and spatial diversity trade-offs that must be made during task planning. Compressed sensing theory argues that the mutual coherence of the measurement probes is related to the reconstruction performance of sparse domains. With this motivation we compare the mutual coherence and corresponding reconstruction behavior of various mono-static and ultra-narrow band multi-static configurations, which trade-off frequency for geometric diversity. We investigate if such simple metrics are related to SAR reconstruction quality in an obvious way.

Compressed Sensing of Monostatic and Multistatic SAR

In this letter, we study the impact of compressed data collections from a synthetic aperture radar (SAR) sensor on the reconstruction quality of a scene of interest. Different monostatic and multistatic SAR measurement configurations produce different Fourier sampling patterns. These patterns reflect different spectral and spatial diversity tradeoffs that must be made during task planning. Compressed sensing theory argues that the mutual coherence of the measurement probes is related to the reconstruction performance of sparse domains. With this motivation, we propose a closely related t%-average mutual coherence parameter as a sensing configuration quality parameter and examine its relationship to the reconstruction behavior of various monostatic and ultranarrow-band multistatic configurations. We investigate how this easily computed metric is related to SAR reconstruction quality.

Compressed sensing in optical coherence tomography

Optical coherence tomography (OCT) is a valuable technique for non-invasive imaging in medicine and biology. In some applications, conventional time-domain OCT (TD-OCT) has been supplanted by spectral-domain OCT (SD-OCT); the latter uses an apparatus that contains no moving parts and can achieve orders of magnitude faster imaging. This enhancement comes at a cost, however: the CCD array detectors required for SD-OCT are more expensive than the simple photodiodes used in TD-OCT. We explore the possibility of extending the notion of compressed sensing (CS) to SD-OCT, potentially allowing the use of smaller detector arrays. CS techniques can yield accurate signal reconstructions from highly undersampled measurements, i.e., data sampled significantly below the Nyquist rate. The Fourier relationship between the measurements and the desired signal in SD-OCT makes it a good candidate for compressed sensing. Fourier measurements represent good linear projections for the compressed sensing of sparse point-like signals by random under-sampling of frequency-domain data, and axial scans in OCT are generally sparse in nature. This sparsity property has recently been used for the reduction of speckle in OCT images. We have carried out simulations to demonstrate the usefulness of compressed sensing for simplifying detection schemes in SD-OCT. In particular, we demonstrate the reconstruction of a sparse axial scan by using fewer than 10 percent of the measurements required by standard SD-OCT.

A Spatio-Temporal Deconvolution Method to Improve Perfusion CT Quantification

Perfusion imaging is a useful adjunct to anatomic imaging in numerous diagnostic and therapy-monitoring settings. One approach to perfusion imaging is to assume a convolution relationship between a local arterial input function and the tissue enhancement profile of the region of interest via a ¿residue function¿ and subsequently solve for this residue function. This ill-posed problem is generally solved using singular-value decomposition based approaches, and the hemodynamic parameters are solved for each voxel independently. In this paper, we present a formulation which incorporates both spatial and temporal correlations, and show through simulations that this new formulation yields higher accuracy and greater robustness with respect to image noise. We also show using rectal cancer tumor images that this new formulation results in better segregation of normal and cancerous voxels.

Silhouette recognition using high-resolution pursuit

This paper introduces a simple new approach to object recognition from silhouettes. This new approach utilizes features extracted using an adaptive approximation technique called high-resolution pursuit (HRP). In this work, a comparatively small set of HRP features and a simple recognition scheme are used. We demonstrate the strengths of the HRP-based recognition scheme by discriminating among 17 military aircraft. The HRP-based algorithm matches the performance of a widely studied method based on Fourier descriptors in the presence of boundary, scale and orientation variations, and surpasses the performance of the Fourier descriptor-based algorithm in the presence of occlusion and localized silhouette variations.

The sources of sodium escaping from Io revealed by spectral high definition imaging.

On Jupiter’s moon Io, volcanic plumes and evaporating lava flows provide hot gases to form an atmosphere that is subsequently ionized. Some of Io’s plasma is captured by the planet’s strong magnetic field to form a co-rotating torus at Io’s distance; the remaining ions and electrons form Io’s ionosphere. The torus and ionosphere are also depleted by three time-variable processes that produce a banana-shaped cloud orbiting with Io, a giant nebula extending out to about 500 Jupiter radii, and a jet close to Io. No spatial constraints exist for the sources of the first two; they have been inferred only from modelling the patterns seen in the trace gas sodium observed far from Io. Here we report observations that reveal a spatially confined stream that ejects sodium only from the wake of the Io–torus interaction, together with a visually distinct, spherically symmetrical outflow region arising from atmospheric sputtering. The spatial extent of the ionospheric wake that feeds the stream is more than twice that observed by the Galileo spacecraft and modelled successfully. This implies considerable variability, and therefore the need for additional modelling of volcanically-driven, episodic states of the great jovian nebula.

An Interferometric Reflectance Imaging Sensor for Point of Care Viral Diagnostics

The use of in vitro diagnostic devices is transitioning from the laboratory to the primary care setting to address early disease detection needs. Time critical viral diagnoses are often made without support due to the experimental time required in todays standard tests. Available rapid point of care (POC) viral tests are less reliable, requiring a follow-on confirmatory test before conclusions can be drawn. The development of a reliable POC viral test for the primary care setting would decrease the time for diagnosis leading to a lower chance of transmission and improve recovery. The single particle interferometric reflectance imaging sensor (SP-IRIS) has been shown to be a sensitive and specific-detection platform in serum and whole blood. This paper presents a step towards a POC viral assay through a SP-IRIS prototype with automated data acquisition and analysis and a simple, easy-to-use software interface. Decreasing operation complexity highlights the potential of SP-IRIS as a sensitive and specific POC diagnostic tool. With the integration of a microfluidic cartridge, this automated instrument will allow an untrained user to run a sample-to-answer viral assay in the POC setting.

A decomposition-based CT reconstruction formulation for reducing blooming artifacts

Cardiac computed tomography represents an important advancement in the ability to assess coronary vessels. The accuracy of these non-invasive imaging studies is limited, however, by the presence of calcium, since calcium blooming artifacts lead to an over-estimation of the degree of luminal narrowing. To address this problem, we have developed a unified decomposition-based iterative reconstruction formulation, where different penalty functions are imposed on dense objects (i.e. calcium) and soft tissue. The result is a quantifiable reduction in blooming artifacts without the introduction of new distortions away from the blooming observed in other methods. Results are shown for simulations, phantoms, ex vivo, and in vivo studies.

Sparsity driven ultrasound imaging.

An image formation framework for ultrasound imaging from synthetic transducer arrays based on sparsity-driven regularization functionals using single-frequency Fourier domain data is proposed. The framework involves the use of a physics-based forward model of the ultrasound observation process, the formulation of image formation as the solution of an associated optimization problem, and the solution of that problem through efficient numerical algorithms. The sparsity-driven, model-based approach estimates a complex-valued reflectivity field and preserves physical features in the scene while suppressing spurious artifacts. It also provides robust reconstructions in the case of sparse and reduced observation apertures. The effectiveness of the proposed imaging strategy is demonstrated using experimental data.

Accurate model-based high resolution cardiac image reconstruction in dual source CT

Cardiac imaging represents one of the most challenging imaging problems, requiring high spatial and temporal resolutions along with good tissue contrast. One of the newest clinical cardiac CT scanners incorporates two source-detector pairs in order to improve the temporal resolution by two-fold. To achieve the highest spatial resolution, reconstructions using iterative techniques may be desired. Yet the complexity of the dual-source geometry makes accurate system modeling a challenge. In this paper, we present a model-based iterative reconstruction algorithm for the dual-source CT. We demonstrate, using a total variation formulation, the results of our reconstructions. To accelerate the processing and enhance the quality of the result, we also incorporate a simplified detector response function in the forward projector. A segment of heavily-calcified coronary artery is used to demonstrate the spatial and temporal resolution of this approach with the dual-source system.