We investigate the feasibility of trans-rectal optical tomography of the prostate using an endo-rectal near-infrared (NIR) applicator that is to be integrated with a trans-rectal ultrasound (TRUS) probe. Integration with TRUS ensures accurate endo-rectal positioning of the NIR applicator and the utility of using TRUS spatial prior information to guide NIR image reconstruction. The prostate NIR image reconstruction is challenging even with the use of spatial prior owing to the anatomic complexity of the imaging domain. A hierarchical reconstruction algorithm is developed that implements cascaded initial-guesses for nested domains. This hierarchical image reconstruction method is then applied to evaluating a number of NIR applicator designs for integration with a sagittal TRUS transducer. A NIR applicator configuration feasible for instrumentation development is proposed that contains one linear array of optodes on each lateral side of the sagittal TRUS transducer. The performance of this NIR applicator is characterized for the recovery of single tumor mimicking lesion as well as dual targets in the prostate. The results suggest a strong feasibility of transrectal prostate imaging by use of the endo-rectal NIR/US probe.

Near-infrared optical tomography is an interesting technique of imaging with high blood-based contrast. Unfortunately non-invasive NIR tomographic imaging has been restricted to specific organs like breast that can be transilluminated externally. In this paper, we demonstrate that near-infrared (NIR) optical tomography can be employed at the endoscopescale, and implemented at a rapid sampling speed that allows translation to in vivo use. A spread-spectral-encoding technique based on a broadband light source is combined with light delivery by linear-to-circular fiber bundle, to provide endoscopic probing of multiple source/detector fibers for tomographic imaging as well as parallel sampling of all sourcedetector pairs for rapid data acquisition. Endoscopic NIR tomography is demonstrated by use of a 12mm diameter probe housing 8 sources and 8 detectors at 8 Hz frame rate. Transrectal NIR optical tomography by use of tissue specimen is also presented. This novel approach provides the key feasibility studies to allow this blood-based contrast imaging technology to be tried in cancer detection of internal organs via endoscopic interrogation.

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Endoscopic near-infrared (NIR) optical tomography is a novel approach that allows the blood-based high intrinsic optical contrast to be imaged for the detection of cancer in internal organs. In endoscopic NIR tomography, the imaging array is arranged within the interior of the medium as opposed to the exterior as seen in conventional NIR tomography approaches. The source illuminates outward from the circular NIR probe, and the detector collects the diffused light from the medium surrounding the NIR probe. This new imaging geometry may involve forward and inverse approaches that are significantly different from those used in conventional NIR tomography. The implementation of a hollowcentered forward mesh within the context of conventional NIR tomography reconstruction has already led to the first demonstration of endoscopic NIR optical tomography. This paper presents some fundamental computational aspects regarding the performance and sensitivity of this endoscopic NIR tomography configuration. The NIRFAST modeling and image reconstruction package developed for conventional circular NIR geometry is used for endoscopic NIR tomography, and initial quantitative analysis has been conducted to investigate the "effective" imaging depth, required mesh resolution, and limit in contrast resolution, among other parameters. This study will define the performance expected and may provide insights into hardware requirements needed for revision of NIRFAST for the endoscopic NIR tomography geometry.

Synthetic aperture radar systems that use the polar format algorithm are subject to a focused scene size limit inherent to the polar format algorithm. The classic focused scene size limit is determined from the dominant residual range phase error term. Given the many sources of phase error in a synthetic aperture radar, a system designer is interested in how much phase error results from the assumptions made with the polar format algorithm. Autofocus algorithms have limits to the amount and type of phase error that can be corrected. Current methods correct only one or a few terms of the residual phase error. A system designer needs to be able to evaluate the contribution of the residual or uncorrected phase error terms to determine the new focused scene size limit. This paper describes a method to estimate the complete residual phase error, not just one or a few of the dominant residual terms. This method is demonstrated with polar format image formation, but is equally applicable to other image formation algorithms. A benefit for the system designer is that additional correction terms can be added or deleted from the analysis as necessary to evaluate the resulting effect upon image quality.

Synthetic aperture radar (SAR) images contain a grainy pattern, called speckle, that is a consequence of a coherent imaging system. For fine resolution SAR images speckle can obscure subtle features and reduce visual appeal. Many speckle reduction methods result in a loss of image resolution and reduce visual appeal which can obscure subtle features. Another approach to maintain resolution while reducing speckle is to register and combine multiple images. For persistent surveillance applications it is more efficient for an airborne platform to fly circles around the particular area of interest. In these cases, it would be beneficial to combine multiple circle mode SAR images, however the image registration process is not so straightforward because the layover angle changes in each image.This paper develops a SAR image registration process for combining multiple circle mode SAR images to reduce speckle while preserving resolution. The registration first uses a feature matching algorithm for a coarse rotation and alignment, and then uses a fine registration and warp. Ku band SAR data from a circle mode SAR collection is used to show the effectiveness of the registration and enhanced visual appeal from multi-looking.

Interference and interference mitigation techniques degrade synthetic aperture radar (SAR) coherent data products. Radars utilizing stretch processing present a unique challenge for many mitigation techniques because the interference signal itself is modified through stretch processing from its original signal characteristics. Many sources of interference, including constant tones, are only present within the fast-time sample data for a limited number of samples, depending on the radar and interference bandwidth. Adaptive filtering algorithms to estimate and remove the interference signal that rely upon assuming stationary interference signal characteristics can be ineffective. An effective mitigation method, called notching, forces the value of the data samples containing interference to zero. However, as the number of data samples set to zero increases, image distortion and loss of resolution degrade both the image product and any second order image products.Techniques to repair image distortions, 1 are effective for point-like targets. However, these techniques are not designed to model and repair distortions in SAR image terrain. Good terrain coherence is important for SAR second order image products because terrain occupies the majority of many scenes. For the case of coherent change detection it is the terrain coherence itself that determines the quality of the change detection image. This paper proposes an unique equalization technique that improves coherence over existing notching techniques. First, the proposed algorithm limits mitigation to only the samples containing interference, unlike adaptive filtering algorithms, so the remaining samples are not modified. Additionally, the mitigation adapts to changing interference power such that the resulting correction equalizes the power across the data samples. The result is reduced distortion and improved coherence for the terrain. SAR data demonstrates improved coherence from the proposed equalization correction over existing notching methods for chirped interference sources.

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