Modeling the Anisotropic Resolution and Noise Properties of Digital Breast Tomosynthesis

Digital breast tomosynthesis (DBT) is a 3D imaging modality in which a reconstruction of the breast is generated from various x-ray projections. Due to the newness of this technology, the development of an analytical model of image quality has been on-going. In this thesis, a more complete model is developed by addressing the limitations found in the previous linear systems (LS) model [Zhao, Med. Phys. 2008, 35(12): 5219-32]. A central assumption of the LS model is that the angle of x-ray incidence is approximately normal to the detector in each projection. To model the effect of oblique x-ray incidence, this thesis generalizes Swank\u27s calculations of the transfer functions of x-ray fluorescent screens to arbitrary incident angles. In the LS model, it is also assumed that the pixelation in the reconstruction grid is the same as the detector; hence, the highest frequency that can be resolved is the detector alias frequency. This thesis considers reconstruction grids with smaller pixelation to investigate super-resolution, or visibility of higher frequencies. A sine plate is introduced as a conceptual test object to analyze super-resolution. By orienting the long axis of the sine plate at various angles, the feasibility of oblique reconstruction planes is also investigated. This formulation differs from the LS model in which reconstruction planes are parallel to the breast support. It is shown that the transfer functions for arbitrary angles of x-ray incidence can be modeled in closed form. The high frequency modulation transfer function (MTF) and detective quantum efficiency (DQE) are degraded due to oblique x-ray incidence. In addition, using the sine plate, it is demonstrated that a reconstruction can resolve frequencies exceeding the detector alias frequency. Experimental images of bar patterns verified the existence of super-resolution. Anecdotal clinical examples showed that super-resolution improves the visibility of microcalcifications. The feasibility of oblique reconstructions was established theoretically with the sine plate and was validated experimentally with bar patterns. This thesis develops a more complete model of image quality in DBT by addressing the limitations of the LS model. In future studies, this model can be used as a tool for optimizing DBT

A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction

The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow. Inspired by recent advances in deep learning, we propose a framework for reconstructing MR images from undersampled data using a deep cascade of convolutional neural networks to accelerate the data acquisition process. We show that for Cartesian undersampling of 2D cardiac MR images, the proposed method outperforms the state-of-the-art compressed sensing approaches, such as dictionary learning-based MRI (DLMRI) reconstruction, in terms of reconstruction error, perceptual quality and reconstruction speed for both 3-fold and 6-fold undersampling. Compared to DLMRI, the error produced by the method proposed is approximately twice as small, allowing to preserve anatomical structures more faithfully. Using our method, each image can be reconstructed in 23 ms, which is fast enough to enable real-time applications

Single frame super-resolution image system

The estimation of some unknown quantity information from known observable information can be viewed as a specific statistical process which needs an extra source of information prediction strategy. In this regard, image super-resolution is an important application In this thesis, we proposed a new image interpolation method based on Redundant Discrete Wavelet Transform (RDWT) and self-adaptive processes in which edge direction details are considered to solve single-frame image super-resolution task. Information about sharp variations, both in horizontal and vertical directions derived from wavelet transform sub-bands are considered, followed by detection and modification of the aliasing part in the preliminary output in order to increase the visual effect. By exploiting fundamental properties of images such as property of edge direction, different parts of the source image are considered separately in order to predict the vertical and horizontal details accurately, helping to consummate the whole framework in reconstructing the high-resolution image. Extensive tests of the proposed method show that both objective quality (PSNR) and subjective quality are obviously improved compared to several other state-of-the-art methods. And this work also leaved capacious space for further research, not only theoretical but also practical. Some of the related research applications based on this algorithm strategy are also briefly introduced

High-Resolution Building and Road Detection from Sentinel-2

Mapping buildings and roads automatically with remote sensing typically requires high-resolution imagery, which is expensive to obtain and often sparsely available. In this work we demonstrate how multiple 10 m resolution Sentinel-2 images can be used to generate 50 cm resolution building and road segmentation masks. This is done by training a `student' model with access to Sentinel-2 images to reproduce the predictions of a `teacher' model which has access to corresponding high-resolution imagery. While the predictions do not have all the fine detail of the teacher model, we find that we are able to retain much of the performance: for building segmentation we achieve 78.3% mIoU, compared to the high-resolution teacher model accuracy of 85.3% mIoU. We also describe a related method for counting individual buildings in a Sentinel-2 patch which achieves R^2 = 0.91 against true counts. This work opens up new possibilities for using freely available Sentinel-2 imagery for a range of tasks that previously could only be done with high-resolution satellite imagery

Color Reconstruction and Resolution Enhancement Using Super-Resolution

Image super-resolution (SR) is a process that enhances the resolution of an image or a set of images beyond the resolution of the imaging sensor. Although there are several super-resolution methods, fusion super-resolution techniques are well suited for real-time implementations. In fusion super-resolution, the high-resolution images are reconstructed using different low-resolution-observed images, thereby increasing the high-frequency information and decreasing the degradation caused by the low-resolution sampling process. In terms of color reconstruction, standard reconstruction algorithms usually perform a bilinear interpolation of each color. This reconstruction performs a strong low-pass filtering, removing most of the aliasing present in the luminance signal. In this chapter, a novel way of color reconstruction is presented by using super-resolution in order to reconstruct the missing colors

Three Super-Earths Orbiting HD 7924

We report the discovery of two super-Earth mass planets orbiting the nearby K0.5 dwarf HD 7924 which was previously known to host one small planet. The new companions have masses of 7.9 and 6.4 M$_\oplus$, and orbital periods of 15.3 and 24.5 days. We perform a joint analysis of high-precision radial velocity data from Keck/HIRES and the new Automated Planet Finder Telescope (APF) to robustly detect three total planets in the system. We refine the ephemeris of the previously known planet using five years of new Keck data and high-cadence observations over the last 1.3 years with the APF. With this new ephemeris, we show that a previous transit search for the inner-most planet would have covered 70% of the predicted ingress or egress times. Photometric data collected over the last eight years using the Automated Photometric Telescope shows no evidence for transits of any of the planets, which would be detectable if the planets transit and their compositions are hydrogen-dominated. We detect a long-period signal that we interpret as the stellar magnetic activity cycle since it is strongly correlated with the Ca II H and K activity index. We also detect two additional short-period signals that we attribute to rotationally-modulated starspots and a one month alias. The high-cadence APF data help to distinguish between the true orbital periods and aliases caused by the window function of the Keck data. The planets orbiting HD 7924 are a local example of the compact, multi-planet systems that the Kepler Mission found in great abundance.Comment: Accepted to ApJ on 4/7/201

Searching for transits in the Wide Field Camera Transit Survey with difference-imaging light curves

The Wide Field Camera Transit Survey is a pioneer program aiming at for searching extra-solar planets in the near-infrared. The images from the survey are processed by a data reduction pipeline, which uses aperture photometry to construct the light curves. We produce an alternative set of light curves using the difference-imaging method for the most complete field in the survey and carry out a quantitative comparison between the photometric precision achieved with both methods. The results show that differencephotometry light curves present an important improvement for stars with J > 16. We report an implementation on the box-fitting transit detection algorithm, which performs a trapezoid-fit to the folded light curve, providing more accurate results than the boxfitting model. We describe and optimize a set of selection criteria to search for transit candidates, including the V-shape parameter calculated by our detection algorithm. The optimized selection criteria are applied to the aperture photometry and difference-imaging light curves, resulting in the automatic detection of the best 200 transit candidates from a sample of ~475 000 sources. We carry out a detailed analysis in the 18 best detections and classify them as transiting planet and eclipsing binary candidates. We present one planet candidate orbiting a late G-type star. No planet candidate around M-stars has been found, confirming the null detection hypothesis and upper limits on the occurrence rate of short-period giant planets around M-dwarfs presented in a prior study. We extend the search for transiting planets to stars with J ≤ 18, which enables us to set a stricter upper limit of 1.1%. Furthermore, we present the detection of five faint extremely-short period eclipsing binaries and three M-dwarf/M-dwarf binary candidates. The detections demonstrate the benefits of using the difference-imaging light curves, especially when going to fainter magnitudes.Peer reviewe