Chaotic Compressed Sensing and Its Application to Magnetic Resonance Imaging

Fast image acquisition in magnetic resonance imaging (MRI) is important, due to the need to find ways that help relieve patient’s stress during MRI scans. Methods for fast MRI have been proposed, most notably among them are pMRI (parallel MRI), SWIFT (SWeep Imaging with Fourier Transformation), and compressed sensing (CS) based MRI. Although it promises to significantly reduce acquisition time, applying CS to MRI leads to difficulties with hardware design because of the randomness nature of the measurement matrix used by the conventional CS methods. In this paper, we propose a novel method that combines the above-mentioned three approaches for fast MRI by designing a compound measurement matrix from a series of single measurement matrices corresponding to pMRI, SWIFT, and CS. In our method, the CS measurement matrix is designed to be deterministic via chaotic systems. This chaotic compressed sensing (CCS) measurement matrix, while retaining most features of the random CS matrix, is simpler to realize in hardware. Several compound measurement matrices have been constructed and examined in this work, including CCS-MRI, CCS-pMRI, CCS-SWIFT, and CCS-pSWIFT. Simulation results showed that the proposed method allows an increase in the speed of the MRI acquisition process while not compromising the quality of the acquired MR images

Development of a light-powered microstructure : enhancing thermal actuation with near-infrared absorbent gold nanoparticles.

Development of microscale actuating technologies has considerably added to the toolset for interacting with natural components at the cellular level. Small-scale actuators and switches have potential in areas such as microscale pumping and particle manipulation. Thermal actuation has been used with asymmetric geometry to create large deflections with high force relative to electrostatically driven systems. However, many thermally based techniques require a physical connection for power and operate outside the temperature range conducive for biological studies and medical applications. The work presented here describes the design of an out-of-plane bistable switch that responds to near-infrared light with wavelength-specific response. In contrast to thermal actuating principles that require wired conductive components for Joule heating, the devices shown here are wirelessly powered by near -infrared (IR) light by patterning a wavelength-specific absorbent gold nanoparticle (GNP) film onto the microstructure. An optical window exists which allows near-IR wavelength light to permeate living tissue, and high stress mismatch in the bilayer geometry allows for large actuation at biologically acceptable limits. Patterning the GNP film will allow thermal gradients to be created from a single laser source, and integration of various target wavelengths will allow for microelectromechanical (MEMS) devices with multiple operating modes. An optically induced temperature gradient using wavelength-selective printable or spinnable coatings would provide a versatile method of wireless and non-invasive thermal actuation. This project aims to provide a fundamental understanding of the particle and surface interaction for bioengineering applications based on a “hybrid” of infrared resonant gold nanoparticles and MEMS structures. This hybrid technology has potential applications in light-actuated switches and other mechanical structures. Deposition methods and surface chemistry are integrated with three-dimensional MEMS structures in this work. The long-term goal of this project is a system of light-powered microactuators for exploring cells\u27 response to mechanical stimuli, adding to the fundamental understanding of tissue response to everyday mechanical stresses at the molecular level

Chaotic Sensing

We propose a sparse imaging methodology called Chaotic Sensing (ChaoS) that enables the use of limited yet deterministic linear measurements through fractal sampling. A novel fractal in the discrete Fourier transform is introduced that always results in the artefacts being turbulent in nature. These chaotic artefacts have characteristics that are image independent, facilitating their removal through dampening (via image denoising) and obtaining the maximum likelihood solution. In contrast with existing methods, such as compressed sensing, the fractal sampling is based on digital periodic lines that form the basis of discrete projected views of the image without requiring additional transform domains. This allows the creation of finite iterative reconstruction schemes in recovering an image from its fractal sampling that is also new to discrete tomography. As a result, ChaoS supports linear measurement and optimisation strategies, while remaining capable of recovering a theoretically exact representation of the image. We apply the method to simulated and experimental limited magnetic resonance (MR) imaging data, where restrictions imposed by MR physics typically favour linear measurements for reducing acquisition time

Developing novel fluorescent probe for peroxynitrite: implication for understanding the roles of peroxynitrite and drug discovery in cerebral ischemia reperfusion injury

Session 7 - Oral PresentationsSTUDY GOAL: Peroxynitrite (ONOO‐) is a cytotoxic factor. As its short lifetime, ONOO‐ is hard to be detected in biological systems. This study aims to develop novel probe for detecting ONOO‐ and understand the roles of ONOO‐ in ischemic brains and drug discovery ABSTRACT: MitoPN‐1 was found to be a ONOO‐ specific probe with no toxicity. With MitoPN‐1, we studied the roles of ONOO‐ in hypoxic neuronal cells in vitro and MCAO …postprin

Multidimensional Data Processing for Optical Coherence Tomography Imaging

Optical Coherence Tomography (OCT) is a medical imaging technique which distinguishes itself by acquiring microscopic resolution images in-vivo at millimeter scale fields of view. The resulting in images are not only high-resolution, but often multi-dimensional to capture 3-D biological structures or temporal processes. The nature of multi-dimensional data presents a unique set of challenges to the OCT user that include acquiring, storing, and handling very large datasets, visualizing and understanding the data, and processing and analyzing the data. In this dissertation, three of these challenges are explored in depth: sub-resolution temporal analysis, 3-D modeling of fiber structures, and compressed sensing of large, multi-dimensional datasets. Exploration of these problems is followed by proposed solutions and demonstrations which rely on tools from multiple research areas including digital image filtering, image de-noising, and sparse representation theory. Combining approaches from these fields, advanced solutions were developed to produce new and groundbreaking results. High-resolution video data showing cilia motion in unprecedented detail and scale was produced. An image processing method was used to create the first 3-D fiber model of uterine tissue from OCT images. Finally, a compressed sensing approach was developed which we show to guarantee high accuracy image recovery of more complicated, clinically relevant, samples than had been previously demonstrated. The culmination of these methods represents a step forward in OCT image analysis, showing that these cutting edge tools can also be applied to OCT data and in the future be employed in a clinical setting

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas