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- Creators: Arizona State University
- Creators: Alkhateeb, Ahmed
- Status: Published
Description
Magnetic Resonance Imaging using spiral trajectories has many advantages in speed, efficiency in data-acquistion and robustness to motion and flow related artifacts. The increase in sampling speed, however, requires high performance of the gradient system. Hardware inaccuracies from system delays and eddy currents can cause spatial and temporal distortions in the encoding gradient waveforms. This causes sampling discrepancies between the actual and the ideal k-space trajectory. Reconstruction assuming an ideal trajectory can result in shading and blurring artifacts in spiral images. Current methods to estimate such hardware errors require many modifications to the pulse sequence, phantom measurements or specialized hardware. This work presents a new method to estimate time-varying system delays for spiral-based trajectories. It requires a minor modification of a conventional stack-of-spirals sequence and analyzes data collected on three orthogonal cylinders. The method is fast, robust to off-resonance effects, requires no phantom measurements or specialized hardware and estimate variable system delays for the three gradient channels over the data-sampling period. The initial results are presented for acquired phantom and in-vivo data, which show a substantial reduction in the artifacts and improvement in the image quality.
ContributorsBhavsar, Payal (Author) / Pipe, James G (Thesis advisor) / Frakes, David (Committee member) / Kodibagkar, Vikram (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation describes development of a procedure for obtaining high quality, optical grade sand coupons from frozen sand specimens of Ottawa 20/30 sand for image processing and analysis to quantify soil structure along with a methodology for quantifying the microstructure from the images. A technique for thawing and stabilizing frozen core samples was developed using optical grade Buehler® Epo-Tek® epoxy resin, a modified triaxial cell, a vacuum/reservoir chamber, a desiccator, and a moisture gauge. The uniform epoxy resin impregnation required proper drying of the soil specimen, application of appropriate confining pressure and vacuum levels, and epoxy mixing, de-airing and curing. The resulting stabilized sand specimen was sectioned into 10 mm thick coupons that were planed, ground, and polished with progressively finer diamond abrasive grit levels using the modified Allied HTP Inc. polishing method so that the soil structure could be accurately quantified using images obtained with the use of an optical microscopy technique. Illumination via Bright Field Microscopy was used to capture the images for subsequent image processing and sand microstructure analysis. The quality of resulting images and the validity of the subsequent image morphology analysis hinged largely on employment of a polishing and grinding technique that resulted in a flat, scratch free, reflective coupon surface characterized by minimal microstructure relief and good contrast between the sand particles and the surrounding epoxy resin. Subsequent image processing involved conversion of the color images first to gray scale images and then to binary images with the use of contrast and image adjustments, removal of noise and image artifacts, image filtering, and image segmentation. Mathematical morphology algorithms were used on the resulting binary images to further enhance image quality. The binary images were then used to calculate soil structure parameters that included particle roundness and sphericity, particle orientation variability represented by rose diagrams, statistics on the local void ratio variability as a function of the sample size, and the local void ratio distribution histograms using Oda's method and Voronoi tessellation method, including the skewness, kurtosis, and entropy of a gamma cumulative probability distribution fit to the local void ratio distribution.
ContributorsCzupak, Zbigniew David (Author) / Kavazanjian, Edward (Thesis advisor) / Zapata, Claudia (Committee member) / Houston, Sandra (Committee member) / Arizona State University (Publisher)
Created2011
Description
The Arizona State University Herbarium began in 1896 when Professor Fredrick Irish collected the first recorded Arizona specimen for what was then called the Tempe Normal School - a Parkinsonia microphylla. Since then, the collection has grown to approximately 400,000 specimens of vascular plants and lichens. The most recent project includes the digitization - both the imaging and databasing - of approximately 55,000 vascular plant specimens from Latin America. To accomplish this efficiently, possibilities in non-traditional methods, including both new and existing technologies, were explored. SALIX (semi-automatic label information extraction) was developed as the central tool to handle automatic parsing, along with BarcodeRenamer (BCR) to automate image file renaming by barcode. These two developments, combined with existing technologies, make up the SALIX Method. The SALIX Method provides a way to digitize herbarium specimens more efficiently than the traditional approach of entering data solely through keystroking. Using digital imaging, optical character recognition, and automatic parsing, I found that the SALIX Method processes data at an average rate that is 30% faster than typing. Data entry speed is dependent on user proficiency, label quality, and to a lesser degree, label length. This method is used to capture full specimen records, including close-up images where applicable. Access to biodiversity data is limited by the time and resources required to digitize, but I have found that it is possible to do so at a rate that is faster than typing. Finally, I experiment with the use of digital field guides in advancing access to biodiversity data, to stimulate public engagement in natural history collections.
ContributorsBarber, Anne Christine (Author) / Landrum, Leslie R. (Thesis advisor) / Wojciechowski, Martin F. (Thesis advisor) / Gilbert, Edward (Committee member) / Lafferty, Daryl (Committee member) / Arizona State University (Publisher)
Created2012
Description
The challenge of radiation therapy is to maximize the dose to the tumor while simultaneously minimizing the dose elsewhere. Proton therapy is well suited to this challenge due to the way protons slow down in matter. As the proton slows down, the rate of energy loss per unit path length continuously increases leading to a sharp dose near the end of range. Unlike conventional radiation therapy, protons stop inside the patient, sparing tissue beyond the tumor. Proton therapy should be superior to existing modalities, however, because protons stop inside the patient, there is uncertainty in the range. “Range uncertainty” causes doctors to take a conservative approach in treatment planning, counteracting the advantages offered by proton therapy. Range uncertainty prevents proton therapy from reaching its full potential.
A new method of delivering protons, pencil-beam scanning (PBS), has become the new standard for treatment over the past few years. PBS utilizes magnets to raster scan a thin proton beam across the tumor at discrete locations and using many discrete pulses of typically 10 ms duration each. The depth is controlled by changing the beam energy. The discretization in time of the proton delivery allows for new methods of dose verification, however few devices have been developed which can meet the bandwidth demands of PBS.
In this work, two devices have been developed to perform dose verification and monitoring with an emphasis placed on fast response times. Measurements were performed at the Mayo Clinic. One detector addresses range uncertainty by measuring prompt gamma-rays emitted during treatment. The range detector presented in this work is able to measure the proton range in-vivo to within 1.1 mm at depths up to 11 cm in less than 500 ms and up to 7.5 cm in less than 200 ms. A beam fluence detector presented in this work is able to measure the position and shape of each beam spot. It is hoped that this work may lead to a further maturation of detection techniques in proton therapy, helping the treatment to reach its full potential to improve the outcomes in patients.
A new method of delivering protons, pencil-beam scanning (PBS), has become the new standard for treatment over the past few years. PBS utilizes magnets to raster scan a thin proton beam across the tumor at discrete locations and using many discrete pulses of typically 10 ms duration each. The depth is controlled by changing the beam energy. The discretization in time of the proton delivery allows for new methods of dose verification, however few devices have been developed which can meet the bandwidth demands of PBS.
In this work, two devices have been developed to perform dose verification and monitoring with an emphasis placed on fast response times. Measurements were performed at the Mayo Clinic. One detector addresses range uncertainty by measuring prompt gamma-rays emitted during treatment. The range detector presented in this work is able to measure the proton range in-vivo to within 1.1 mm at depths up to 11 cm in less than 500 ms and up to 7.5 cm in less than 200 ms. A beam fluence detector presented in this work is able to measure the position and shape of each beam spot. It is hoped that this work may lead to a further maturation of detection techniques in proton therapy, helping the treatment to reach its full potential to improve the outcomes in patients.
ContributorsHolmes, Jason M (Author) / Alarcon, Ricardo (Thesis advisor) / Bues, Martin (Committee member) / Galyaev, Eugene (Committee member) / Chamberlin, Ralph (Committee member) / Arizona State University (Publisher)
Created2019
Description
There has been much debate in the world of academia over the valuation of conglomerates. This thesis proposes the use of the EVA theory in explaining fluctuations in conglomerates’ valuation, and we believe that ROIC, WACC, and ROIC-WACC are three indicators that to a certain extent explain these valuation fluctuations. Through analysis of a sample containing 23 conglomerates, this thesis finds that ROIC, WACC, and ROIC-WACC exhibit positive correlation with valuation fluctuations. In the case study on Fosun, this thesis finds that ROIC-WACC is highly correlated with Fosun’s valuation fluctuations and next with ROIC. Thus this thesis conjectures that for investment companies for which investment capital is derived largely from insurance float, such as Fosun, ROIC-WACC is a better valuation tool.
ContributorsLiang, Xinjun (Author) / Chen, Hong (Thesis advisor) / Pei, Ker-Wei (Thesis advisor) / Zhu, Ning (Committee member) / Arizona State University (Publisher)
Created2015
Description
To achieve the ambitious long-term goal of a feet of cooperating Flexible Autonomous
Machines operating in an uncertain Environment (FAME), this thesis addresses several
critical modeling, design, control objectives for rear-wheel drive ground vehicles.
Toward this ambitious goal, several critical objectives are addressed. One central objective of the thesis was to show how to build low-cost multi-capability robot platform
that can be used for conducting FAME research.
A TFC-KIT car chassis was augmented to provide a suite of substantive capabilities.
The augmented vehicle (FreeSLAM Robot) costs less than $500 but offers the capability
of commercially available vehicles costing over $2000.
All demonstrations presented involve rear-wheel drive FreeSLAM robot. The following
summarizes the key hardware demonstrations presented and analyzed:
(1)Cruise (v, ) control along a line,
(2) Cruise (v, ) control along a curve,
(3) Planar (x, y) Cartesian Stabilization for rear wheel drive vehicle,
(4) Finish the track with camera pan tilt structure in minimum time,
(5) Finish the track without camera pan tilt structure in minimum time,
(6) Vision based tracking performance with different cruise speed vx,
(7) Vision based tracking performance with different camera fixed look-ahead distance L,
(8) Vision based tracking performance with different delay Td from vision subsystem,
(9) Manually remote controlled robot to perform indoor SLAM,
(10) Autonomously line guided robot to perform indoor SLAM.
For most cases, hardware data is compared with, and corroborated by, model based
simulation data. In short, the thesis uses low-cost self-designed rear-wheel
drive robot to demonstrate many capabilities that are critical in order to reach the
longer-term FAME goal.
Machines operating in an uncertain Environment (FAME), this thesis addresses several
critical modeling, design, control objectives for rear-wheel drive ground vehicles.
Toward this ambitious goal, several critical objectives are addressed. One central objective of the thesis was to show how to build low-cost multi-capability robot platform
that can be used for conducting FAME research.
A TFC-KIT car chassis was augmented to provide a suite of substantive capabilities.
The augmented vehicle (FreeSLAM Robot) costs less than $500 but offers the capability
of commercially available vehicles costing over $2000.
All demonstrations presented involve rear-wheel drive FreeSLAM robot. The following
summarizes the key hardware demonstrations presented and analyzed:
(1)Cruise (v, ) control along a line,
(2) Cruise (v, ) control along a curve,
(3) Planar (x, y) Cartesian Stabilization for rear wheel drive vehicle,
(4) Finish the track with camera pan tilt structure in minimum time,
(5) Finish the track without camera pan tilt structure in minimum time,
(6) Vision based tracking performance with different cruise speed vx,
(7) Vision based tracking performance with different camera fixed look-ahead distance L,
(8) Vision based tracking performance with different delay Td from vision subsystem,
(9) Manually remote controlled robot to perform indoor SLAM,
(10) Autonomously line guided robot to perform indoor SLAM.
For most cases, hardware data is compared with, and corroborated by, model based
simulation data. In short, the thesis uses low-cost self-designed rear-wheel
drive robot to demonstrate many capabilities that are critical in order to reach the
longer-term FAME goal.
ContributorsLu, Xianglong (Author) / Rodriguez, Armando Antonio (Thesis advisor) / Berman, Spring (Committee member) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2016
Description
Readout Integrated Circuits(ROICs) are important components of infrared(IR) imag
ing systems. Performance of ROICs affect the quality of images obtained from IR
imaging systems. Contemporary infrared imaging applications demand ROICs that
can support large dynamic range, high frame rate, high output data rate, at low
cost, size and power. Some of these applications are military surveillance, remote
sensing in space and earth science missions and medical diagnosis. This work focuses
on developing a ROIC unit cell prototype for National Aeronautics and Space Ad
ministration(NASA), Jet Propulsion Laboratory’s(JPL’s) space applications. These
space applications also demand high sensitivity, longer integration times(large well
capacity), wide operating temperature range, wide input current range and immunity
to radiation events such as Single Event Latchup(SEL).
This work proposes a digital ROIC(DROIC) unit cell prototype of 30ux30u size,
to be used mainly with NASA JPL’s High Operating Temperature Barrier Infrared
Detectors(HOT BIRDs). Current state of the art DROICs achieve a dynamic range
of 16 bits using advanced 65-90nm CMOS processes which adds a lot of cost overhead.
The DROIC pixel proposed in this work uses a low cost 180nm CMOS process and
supports a dynamic range of 20 bits operating at a low frame rate of 100 frames per
second(fps), and a dynamic range of 12 bits operating at a high frame rate of 5kfps.
The total electron well capacity of this DROIC pixel is 1.27 billion electrons, enabling
integration times as long as 10ms, to achieve better dynamic range. The DROIC unit
cell uses an in-pixel 12-bit coarse ADC and an external 8-bit DAC based fine ADC.
The proposed DROIC uses layout techniques that make it immune to radiation up to
300krad(Si) of total ionizing dose(TID) and single event latch-up(SEL). It also has a
wide input current range from 10pA to 1uA and supports detectors operating from
Short-wave infrared (SWIR) to longwave infrared (LWIR) regions.
ing systems. Performance of ROICs affect the quality of images obtained from IR
imaging systems. Contemporary infrared imaging applications demand ROICs that
can support large dynamic range, high frame rate, high output data rate, at low
cost, size and power. Some of these applications are military surveillance, remote
sensing in space and earth science missions and medical diagnosis. This work focuses
on developing a ROIC unit cell prototype for National Aeronautics and Space Ad
ministration(NASA), Jet Propulsion Laboratory’s(JPL’s) space applications. These
space applications also demand high sensitivity, longer integration times(large well
capacity), wide operating temperature range, wide input current range and immunity
to radiation events such as Single Event Latchup(SEL).
This work proposes a digital ROIC(DROIC) unit cell prototype of 30ux30u size,
to be used mainly with NASA JPL’s High Operating Temperature Barrier Infrared
Detectors(HOT BIRDs). Current state of the art DROICs achieve a dynamic range
of 16 bits using advanced 65-90nm CMOS processes which adds a lot of cost overhead.
The DROIC pixel proposed in this work uses a low cost 180nm CMOS process and
supports a dynamic range of 20 bits operating at a low frame rate of 100 frames per
second(fps), and a dynamic range of 12 bits operating at a high frame rate of 5kfps.
The total electron well capacity of this DROIC pixel is 1.27 billion electrons, enabling
integration times as long as 10ms, to achieve better dynamic range. The DROIC unit
cell uses an in-pixel 12-bit coarse ADC and an external 8-bit DAC based fine ADC.
The proposed DROIC uses layout techniques that make it immune to radiation up to
300krad(Si) of total ionizing dose(TID) and single event latch-up(SEL). It also has a
wide input current range from 10pA to 1uA and supports detectors operating from
Short-wave infrared (SWIR) to longwave infrared (LWIR) regions.
ContributorsPraveen, Subramanya Chilukuri (Author) / Bakkaloglu, Bertan (Thesis advisor) / Kitchen, Jennifer (Committee member) / Long, Yu (Committee member) / Arizona State University (Publisher)
Created2019
Description
SLAM (Simultaneous Localization and Mapping) is a problem that has existed for a long time in robotics and autonomous navigation. The objective of SLAM is for a robot to simultaneously figure out its position in space and map its environment. SLAM is especially useful and mandatory for robots that want to navigate autonomously. The description might make it seem like a chicken and egg problem, but numerous methods have been proposed to tackle SLAM. Before the rise in the popularity of deep learning and AI (Artificial Intelligence), most existing algorithms involved traditional hard-coded algorithms that would receive and process sensor information and convert it into some solvable sensor-agnostic problem. The challenge for these sorts of methods is having to tackle dynamic environments. The more variety in the environment, the poorer the results. Also due to the increase in computational power and the capability of deep learning-based image processing, visual SLAM has become extremely viable and maybe even preferable to traditional SLAM algorithms. In this research, a deep learning-based solution to the SLAM problem is proposed, specifically monocular visual SLAM which is solving the problem of SLAM purely with a singular camera as the input, and the model is tested on the KITTI (Karlsruhe Institute of Technology & Toyota Technological Institute) odometry dataset.
ContributorsRupaakula, Krishna Sandeep (Author) / Bansal, Ajay (Thesis advisor) / Baron, Tyler (Committee member) / Acuna, Ruben (Committee member) / Arizona State University (Publisher)
Created2023
Description
The objective of this work is to design a novel method for imaging targets and scenes which are not directly visible to the observer. The unique scattering properties of terahertz (THz) waves can turn most building surfaces into mirrors, thus allowing someone to see around corners and various occlusions. In the visible regime, most surfaces are very rough compared to the wavelength. As a result, the spatial coherency of reflected signals is lost, and the geometry of the objects where the light bounced on cannot be retrieved. Interestingly, the roughness of most surfaces is comparable to the wavelengths at lower frequencies (100 GHz – 10 THz) without significantly disturbing the wavefront of the scattered signals, behaving approximately as mirrors. Additionally, this electrically small roughness is beneficial because it can be used by the THz imaging system to locate the pose (location and orientation) of the mirror surfaces, thus enabling the reconstruction of both line-of-sight (LoS) and non-line-of-sight (NLoS) objects.
Back-propagation imaging methods are modified to reconstruct the image of the 2-D scenario (range, cross-range). The reflected signal from the target is collected using a SAR (Synthetic Aperture Radar) set-up in a lab environment. This imaging technique is verified using both full-wave 3-D numerical analysis models and lab experiments.
The novel imaging approach of non-line-of-sight-imaging could enable novel applications in rescue and surveillance missions, highly accurate localization methods, and improve channel estimation in mmWave and sub-mmWave wireless communication systems.
Back-propagation imaging methods are modified to reconstruct the image of the 2-D scenario (range, cross-range). The reflected signal from the target is collected using a SAR (Synthetic Aperture Radar) set-up in a lab environment. This imaging technique is verified using both full-wave 3-D numerical analysis models and lab experiments.
The novel imaging approach of non-line-of-sight-imaging could enable novel applications in rescue and surveillance missions, highly accurate localization methods, and improve channel estimation in mmWave and sub-mmWave wireless communication systems.
ContributorsDoddalla, Sai Kiran kiran (Author) / Trichopoulos, George (Thesis advisor) / Alkhateeb, Ahmed (Committee member) / Zeinolabedinzadeh, Saeed (Committee member) / Aberle, James T., 1961- (Committee member) / Arizona State University (Publisher)
Created2019
Description
In this thesis, the synergy between millimeter-wave (mmWave) imaging and wireless communications is used to achieve high accuracy user localization and mapping (SLAM) mobile users in an uncharted environment. Such capability is enabled by taking advantage of the high-resolution image of both line-of-sight (LoS) and non-line-of-sight (NLoS) objects that mmWave imaging provides, and by utilizing angle of arrival (AoA) and time of arrival (ToA) estimators from communications. The motivations of this work are as follows: first, enable accurate SLAM from a single viewpoint i.e., using only one antenna array at the base station without any prior knowledge of the environment. The second motivation is the ability to localize in NLoS-only scenarios where the user signal may experience more than one reflection until it reaches the base station. As such, this proposed work will not make any assumptions on what region the user is and will use mmWave imaging techniques that will work for both near and far field region of the base station and account for the scattering properties of mmWave. Similarly, a near field signal model is developed to correctly estimate the AoA regardless of the user location.
This SLAM approach is enabled by reconstructing the mmWave image of the environment as seen by the base station. Then, an uplink pilot signal from the user is used to estimate both AoA and ToA of the dominant channel paths. Finally, AoA/ToA information is projected into the mmWave image to fully localize the user. Simulations using full-wave electromagnetic solvers are carried out to emulate an environment both in the near and far field. Then, to validate, an experiment carried in laboratory by creating a simple two-dimensional scenario in the 220-300 GHz range using a synthesized 13-cm linear antenna array formed by using vector network analyzer extenders and a one-dimensional linear motorized stage that replicates the base station. After taking measurements, this method successfully reconstructs the image of the environment and localize the user position with centimeter accuracy.
This SLAM approach is enabled by reconstructing the mmWave image of the environment as seen by the base station. Then, an uplink pilot signal from the user is used to estimate both AoA and ToA of the dominant channel paths. Finally, AoA/ToA information is projected into the mmWave image to fully localize the user. Simulations using full-wave electromagnetic solvers are carried out to emulate an environment both in the near and far field. Then, to validate, an experiment carried in laboratory by creating a simple two-dimensional scenario in the 220-300 GHz range using a synthesized 13-cm linear antenna array formed by using vector network analyzer extenders and a one-dimensional linear motorized stage that replicates the base station. After taking measurements, this method successfully reconstructs the image of the environment and localize the user position with centimeter accuracy.
ContributorsAladsani, Mohammad A M S A (Author) / Trichopoulos, Georgios (Thesis advisor) / Alkhateeb, Ahmed (Committee member) / Balanis, Constantine (Committee member) / Arizona State University (Publisher)
Created2019