Abstract: Correcting pattern noise projection images includes acquiring a set of projection images with an optical tomography system including a processor, where each of the set of projection images is acquired at a different angle of view. A threshold is applied to each projection image produce a set of threshold images. Each threshold image may optionally be dilated to produce a set of dilated images that are summed to form an ensemble image. Each of the dilated images is processed to produce a set of binary images. The set of binary images are summed to form an ensemble mask. The ensemble image is divided by the ensemble mask to yield a background pattern noise image. Each projection image is multiplied by a scaling factor and divided by the background pattern noise to produce a quotient image that is filtered to produce a noise corrected projection image.

Abstract: A system and method for detecting poor quality images in an optical tomography system includes an acquisition apparatus for acquiring a set of pseudo-projection images of an object having a center of mass, where each of the set of pseudo-projection images is acquired at a different angle of view. A reconstruction apparatus is coupled to receive the pseudo-projection images, for reconstruction of the pseudo-projection images into 3D reconstruction images. A quality apparatus is coupled to receive the 3D reconstruction images and operates to detect of selected features that characterize poor quality reconstructions.

Abstract: Correcting pattern noise projection images includes acquiring a set of projection images with an optical tomography system including a processor, where each of the set of projection images is acquired at a different angle of view. A threshold is applied to each projection image produce a set of threshold images. Each threshold image may optionally be dilated to produce a set of dilated images that are summed to form an ensemble image. Each of the dilated images is processed to produce a set of binary images. The set of binary images are summed to form an ensemble mask. The ensemble image is divided by the ensemble mask to yield a background pattern noise image. Each projection image is multiplied by a scaling factor and divided by the background pattern noise to produce a quotient image that is filtered to produce a noise corrected projection image.

Abstract: A near-field scanning microwave microscope images the permittivity and dielectric tunability of bulk and thin film dielectric samples on a length scale of about 1 micron or less. The microscope is sensitive to the linear permittivity, as well as to non-linear dielectric terms, which can be measured as a function of an applied electric field. A versatile finite element model is used for the system, which allows quantitive results to e obtained. The technique is non-destructive and has broadband (0.1-50 GHz) capability.

Abstract: The microscope includes a microwave generator connected to a mismatched transmission line which terminates in a probe with an exposed end. When a sample is brought into close proximity with the exposed end of the probe, the frequencies and quality factors of the standing wave resonances on the transmission line between the source and the probe are modified. The microwave signal reflected from the end of the probe varies as the capacitance between the probe and the sample changes and as the conductivity of the sample changes. Scanning the sample relative to the probe allows generation of an image from the variation of the reflected signal. Alternatively, to image a device with the microscope, a microwave signal is applied to the device, the probe is scanned over the device, and the signal that is picked up is recorded. In a second embodiment, a first lock-in amplifier is used to lock in the microscope at the resonant frequency, and a second lock-in amplifier is used to detect a curvature of the resonance.