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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
231

Diffusion-weighted magnetic resonance imaging techniques

Williams, Catherine F. M. January 1998 (has links)
The aim of this project was to compare and evaluate other, non-EPI, diffusion-weighted MRI (DWI) sequences, through imaging experiments, on a phantom and in vivo, (using a 0.95 T system) and computer simulations, and to develop improved DWI methodology which could be implemented on standard hardware. Pulsed gradient spin echo (PGSE) and diffusion-weighted STEAM are slow multiple shot sequences, with measurement times of several minutes. Both sequences are highly sensitive to patient motion, but motion artifact was virtually eliminated using navigator echo phase correction and EGG triggering when diffusion-sensitisation was in the phase-encoding direction. It was demonstrated that both sequences can provide high quality images and allow accurate and straightforward diffusion-coefficient measurement when an imaging time period in the region of 20-30 minutes is available and when diffusion-sensitisation is required in one or two directions. A third direction of diffusion-sensitisation may be feasible if more sophisticated immobilisation or phase correction techniques are employed. A choice between PGSE or STEAM for a given application should take account of the Ti and T2 values of the imaged tissues, since a higher SNR might be provided by STEAM when the T1T2 ratio is high. A diffusion-weighted CE-FAST sequence was implemented with the novel modification of acquisition of a navigator gradient-echo, which was shown to reduce motion artifact when diffusion-sensitisation was in the phase-encoding direction. However, it has been demonstrated by other workers that unknown signal losses due to motion-induced phase incoherence between signal components may remain. The SNR (normalised with respect to the square root of the imaging time) in the phantom and in white matter was similar to that obtained using PGSE, but an advantage of CE- FAST is that it can be performed in a fraction of the measurement time of PGSE. Diffusion-sensitivity was much higher than in other sequences and the diffusion- attenuation was found to agree with an analysis presented in the literature. However, a major disadvantage of the technique, which precludes its use for many DWI applications, is the requirement of accurate knowledge of Ti, T2 and flip angle in order to calculate the diffusion coefficient or tensor. Prior to a study of diffusion-weighted snapshot FLASH, the effects of magnetisation evolution during snapshot FLASH acquisition on image quality and parameter measurement accuracy were first investigated, through phantom experiments and computer simulations, in the context of a r2-weighted snapshot FLASH sequence. It was demonstrated that magnetisation evolution effects can lead to significant error in parameter measurement, but that this error can be eliminated by using crusher gradients to prevent evolved magnetisation from contributing to the acquired signal. However, qualitative effects are not entirely eliminated, since a significant degree of edge blurring may remain, and there is a 50% loss of SNR inherent to the crusher gradient technique. It was then shown, theoretically and experimentally, that in diffusion-weighted snapshot FLASH, the crusher gradient technique not only addresses the problem of magnetisation evolution, but also eliminates the effect of phase shifts arising during the diffusion-preparation sequence.
232

Tomographic imaging with a scanning laser ophthalmoscope

Vieira, Pedro January 1999 (has links)
Retinal imaging with a confocal scanning laser Ophthalmoscope (cSLO) involves scanning a small laser beam over the retina and constructing an image from the reflected light. By applying the confocal principle, tomographic images can be produced by measuring a sequence of slices at different retinal depths. However, the thickness of such slices, when compared with the retinal thickness, is too large to give useful 3D retinal images, if no processing is done. In this work, a prototype cSLO was modified in terms hardware and software to give the ability of doing the tomographic measurements with the maximum theoretical axial resolution possible. A model eye was built to test the performance of the system. A novel algorithm has been developed which fits a double Gaussian curve to the axial intensity profiles generated from a stack of images slices. The underlying assumption is that the laser light has mainly been reflected by two structures in the retina, the internal limiting membrane and the retinal pigment epithelium. From the fitted curve topographic images and novel thickness images of the retina can be generated. Deconvolution algorithms have also been developed to improve the axial resolution of the system, using a theoretically predicted cSLO point spread function. The technique was evaluated using measurements made on a model eye, four normal eyes and seven eyes containing retinal pathology. The reproducibility, accuracy and physiological measurements obtained, were compared with available published data, and showed good agreement. The difference in the measurements when using a double rather than a single Gaussian model was also analysed.
233

Synthesis of dendritic gadolinium complexes with enhanced relaxivities

O'Halloran, Mark January 2002 (has links)
This thesis deals with the synthesis of dendritic gadolinium complexes based on DOTA, with a view to obtaining enhanced relaxivities. Li addition to the inherently long electronic relaxation time and high paramagnetic moment of the gadolinium (III) ion, the speed of rotation of its complexes in solution is a decisive parameter in the determination of the relaxivity. This parameter is dependent on the molecular mass of the complex. Initially, the enantioselective synthesis of novel a-substituted analogues of DOTA was attempted but was not successful due to difficulties encountered in attaining the tetraalkylation of cyclen and the purification of the products obtained. Therefore, further studies were carried out based on the known [Gd(gDOTA)]" system. The synthesis of three medium M(_W) dendrons, each with a focal primary amino group was carried out. Their structures may be described as dendrimeric analogues of poly(ethylene glycol). Two of these structures were successfully coupled to the gadolinium (III) chelate, [Gd.gDOTA]. The acid-catalysed epimerisation of the statistical distribution of stereoisomers yielded solely the (RRRR)/(SSSS) isomeric pair. This system had previously been shown to undergo fast water exchange. The coupling and deprotection procedure yielded paramagnetic dendritic complexes with molecular weights of 2013 and 3535.Relaxivity measurements were carried out on these systems and the results showed significantly higher relaxivities of 18 and 21 mM(^-1) s(^-1) respectively, compared with a value of 7.8 mM(^-1) s(^-1) for the parent compound. Examination of NMRD profiles for the larger system showed a decrease in the rotational correlation time to 310 ps at 298 K, as expected. However, this was accompanied by an increase in the inner-sphere water exchange lifetime to 570 ns at 298 K. Therefore, although an improvement in relaxivity was obtained through a coupling to the slower rotation of the system in solution, this enhancement was limited by the accompanying decrease in the rate of water exchange. The best fitting procedure of the NMRD profiling procedure revealed the presence of 8 second-sphere water molecules at an average distance of 4Å. The second sphere contribution was shown to be the dominant contributor to the overall relaxivity. This accounted for >50% of the increased relaxivity.
234

Stored-grain Monitoring Utilizing Radio Wave Imaging

Asefi, Mohammad 20 June 2016 (has links)
Storage of large amounts of grain post-harvest is common during drying, distribution and preservation of crops. During storage, where grain is usually held in a large metallic container or bin, changes in temperature, moisture, and insect infestation can cause grain to spoil annual post-harvest crop losses are estimated up to 30% in some countries while Canadian losses of 2% exceed a billion dollars. Currently, locally-sensitive temperature and moisture sensors are a common way to monitor grain bins. Sensors are generally strung on heavy duty cables that can withstand the forces generated when unloading grain. This monitoring method provides a coarse sampling of the storage environment due to system cost and the fact that using many sensor cables would require significantly reinforcing the bin. Further, these cables are not suitable for monitoring stored crops that are dried by a combination of stirring and aeration. Over the past four years, I have developed multiple electromagnetic imaging based grain-monitoring systems with the goals of overcoming the deficiencies of existing sensor technology and allowing farmers and distributors a robust way to preserve our food stores and increase revenue. The proposed technology aims to produce global, quantitative images of grain properties throughout the bin from measurements taken by a few side-mounted antennas used to interrogate the bin contents. To develop this technology intensive research was put into the design of low profile, robust antennas as well as numerical analysis of the effects of different field distributions within conducting boundaries. Both electric and magnetic field sensitive antennas were built and tested in small lab-scale as well as full-scale grain bins to experimentally evaluate the performance of such imaging system. This thesis provides details on different system designs and analysis and describes the advantages and challenges associated with the techniques described. / October 2016
235

On-board Robotic Multi-pinhole SPECT System for Region-of-interest (ROI) Imaging

Yan, Susu January 2014 (has links)
<p>On-board image guidance, such as cone-beam CT (CBCT) and kV/MV 2D imaging, is essential in many radiation therapy procedures, such as intensity modulated radiotherapy (IMRT) and stereotactic body radiation therapy (SBRT). These imaging techniques provide predominantly anatomical information for treatment planning and target localization. Recently, studies have shown that treatment planning based on functional and molecular information about the tumor and surrounding tissue could potentially improve the effectiveness of radiation therapy. However, current on-board imaging systems are limited in their functional and molecular imaging capability. Single Photon Emission Computed Tomography (SPECT) is a candidate to achieve on-board functional and molecular imaging. Traditional SPECT systems typically take 20 minutes or more for a scan, which is too long for on-board imaging. A robotic multi-pinhole SPECT system was proposed in this dissertation to provide shorter imaging time by using a robotic arm to maneuver the multi-pinhole SPECT system around the patient in position for radiation therapy. </p><p>A 49-pinhole collimated SPECT detector and its shielding were designed and simulated in this work using the computer-aided design (CAD) software. The trajectories of robotic arm about the patient, treatment table and gantry in the radiation therapy room and several detector assemblies such as parallel holes, single pinhole and 49 pinholes collimated detector were investigated. The rail mounted system was designed to enable a full range of detector positions and orientations to various crucial treatment sites including head and torso, while avoiding collision with linear accelerator (LINAC), patient table and patient.</p><p>An alignment method was developed in this work to calibrate the on-board robotic SPECT to the LINAC coordinate frame and to the coordinate frames of other on-board imaging systems such as CBCT. This alignment method utilizes line sources and one pinhole projection of these line sources. The model consists of multiple alignment parameters which maps line sources in 3-dimensional (3D) space to their 2-dimensional (2D) projections on the SPECT detector. Computer-simulation studies and experimental evaluations were performed as a function of number of line sources, Radon transform accuracy, finite line-source width, intrinsic camera resolution, Poisson noise and acquisition geometry. In computer-simulation studies, when there was no error in determining angles (&alpha;) and offsets (&rho;) of the measured projections, the six alignment parameters (3 translational and 3 rotational) were estimated perfectly using three line sources. When angles (&alpha;) and offsets (&rho;) were provided by Radon transform, the estimation accuracy was reduced. The estimation error was associated with rounding errors of Radon transform, finite line-source width, Poisson noise, number of line sources, intrinsic camera resolution and detector acquisition geometry. The estimation accuracy was significantly improved by using 4 line sources rather than 3 and also by using thinner line-source projections (obtained by better intrinsic detector resolution). With 5 line sources, median errors were 0.2 mm for the detector translations, 0.7 mm for the detector radius of rotation, and less than 0.5° for detector rotation, tilt and twist. In experimental evaluations, average errors relative to a different, independent registration technique were about 1.8 mm for detector translations, 1.1 mm for the detector radius of rotation (ROR), 0.5° and 0.4° for detector rotation and tilt, respectively, and 1.2° for detector twist. </p><p>Simulation studies were performed to investigate the improvement of imaging sensitivity and accuracy of hot sphere localization for breast imaging of patients in prone position. A 3D XCAT phantom was simulated in the prone position with nine hot spheres of 10 mm diameter added in the left breast. A no-treatment-table case and two commercial prone breast boards, 7 and 24 cm thick, were simulated. Different pinhole focal lengths were assessed for root-mean-square-error (RMSE). The pinhole focal lengths resulting in the lowest RMSE values were 12 cm, 18 cm and 21 cm for no table, thin board, and thick board, respectively. In both no table and thin board cases, all 9 hot spheres were easily visualized above background with 4-minute scans utilizing the 49-pinhole SPECT system while seven of nine hot spheres were visible with the thick board. In comparison with parallel-hole system, our 49-pinhole system shows reduction in noise and bias under these simulation cases. These results correspond to smaller radii of rotation for no-table case and thinner prone board. Similarly, localization accuracy with the 49-pinhole system was significantly better than with the parallel-hole system for both the thin and thick prone boards. Median localization errors for the 49-pinhole system with the thin board were less than 3 mm for 5 of 9 hot spheres, and less than 6 mm for the other 4 hot spheres. Median localization errors of 49-pinhole system with the thick board were less than 4 mm for 5 of 9 hot spheres, and less than 8 mm for the other 4 hot spheres. </p><p>Besides prone breast imaging, respiratory-gated region-of-interest (ROI) imaging of lung tumor was also investigated. A simulation study was conducted on the potential of multi-pinhole, region-of-interest (ROI) SPECT to alleviate noise effects associated with respiratory-gated SPECT imaging of the thorax. Two 4D XCAT digital phantoms were constructed, with either a 10 mm or 20 mm diameter tumor added in the right lung. The maximum diaphragm motion was 2 cm (for 10 mm tumor) or 4 cm (for 20 mm tumor) in superior-inferior direction and 1.2 cm in anterior-posterior direction. Projections were simulated with a 4-minute acquisition time (40 seconds per each of 6 gates) using either the ROI SPECT system (49-pinhole) or reference single and dual conventional broad cross-section, parallel-hole collimated SPECT. The SPECT images were reconstructed using OSEM with up to 6 iterations. Images were evaluated as a function of gate by profiles, noise versus bias curves, and a numerical observer performing a forced-choice localization task. Even for the 20 mm tumor, the 49-pinhole imaging ROI was found sufficient to encompass fully usual clinical ranges of diaphragm motion. Averaged over the 6 gates, noise at iteration 6 of 49-pinhole ROI imaging (10.9 µCi/ml) was approximately comparable to noise at iteration 2 of the two dual and single parallel-hole, broad cross-section systems (12.4 µCi/ml and 13.8 µCi/ml, respectively). Corresponding biases were much lower for the 49-pinhole ROI system (3.8 µCi/ml), versus 6.2 µCi/ml and 6.5 µCi/ml for the dual and single parallel-hole systems, respectively. Median localization errors averaged over 6 gates, for the 10 mm and 20 mm tumors respectively, were 1.6 mm and 0.5 mm using the ROI imaging system and 6.6 mm and 2.3 mm using the dual parallel-hole, broad cross-section system. The results demonstrate substantially improved imaging via ROI methods. One important application may be gated imaging of patients in position for radiation therapy.</p><p>A robotic SPECT imaging system was constructed utilizing a gamma camera detector (Digirad 2020tc) and a robot (KUKA KR150-L110 robot). An imaging study was performed with a phantom (PET CT Phantom<super>TM</super>), which includes 5 spheres of 10, 13, 17, 22 and 28 mm in diameter. The phantom was placed on a flat-top couch. SPECT projections were acquired with a parallel-hole collimator and a single-pinhole collimator both without background in the phantom, and with background at 1/10th the sphere activity concentration. The imaging trajectories of parallel-hole and pinhole collimated detectors spanned 180 degrees and 228 degrees respectively. The pinhole detector viewed a 14.7 cm-diameter common volume which encompassed the 28 mm and 22 mm spheres. The common volume for parallel-hole was a 20.8-cm-diameter cylinder which encompassed all five spheres in the phantom. The maneuverability of the robotic system was tested by navigating the detector to trace the flat-top table while avoiding collision with the table and maintaining the closest possible proximity to the common volume. For image reconstruction, detector trajectories were described by radius-of-rotation and detector rotation angle &#952;. These reconstruction parameters were obtained from the robot base and tool coordinates. The robotic SPECT system was able to maneuver the parallel-hole and pinhole collimated SPECT detectors in close proximity to the phantom, minimizing impact of the flat-top couch on detector to center-of-rotation (COR) distance. In no background case, all five spheres were visible in the reconstructed parallel-hole and pinhole images. In with background case, three spheres of 17, 22 and 28 mm diameter were readily observed with the parallel-hole imaging, and the targeted spheres (22 and 28 mm diameter) were readily observed in the pinhole ROI imaging.</p><p>In conclusion, the proposed on-board robotic SPECT can be aligned to LINAC/CBCT with a single pinhole projection of the line-source phantom. Alignment parameters can be estimated using one pinhole projection of line sources. This alignment method may be important for multi-pinhole SPECT, where relative pinhole alignment may vary during rotation. For single pinhole and multi-pinhole SPECT imaging onboard radiation therapy machines, the method could provide alignment of SPECT coordinates with those of CBCT and the LINAC. In simulation studies of prone breast imaging and respiratory-gated lung imaging, the 49-pinhole detector showed better tumor contrast recovery and localization in a 4-minute scan compared to parallel-hole detector. On-board SPECT could be achieved by a robot maneuvering a SPECT detector about patients in position for radiation therapy on a flat-top couch. The robot inherent coordinate frames could be an effective means to estimate detector pose for use in SPECT image reconstruction.</p> / Dissertation
236

Miniaturized Fluorescence Biosensor for Studying Neuronal Events

Nguyen, Thuvan 16 May 2003 (has links)
When developing new techniques to analyze neuro-chemical microenvironments, it is important to realize the incredible variability in the cellular content and the response to stimulation between cells and within a single cell. Conventional analysis techniques yield an average result to describe the content and function of cells. This approach often misses important information since the onset of pathological conditions is always initiated in a small number of cells. New minimally invasive single cell analysis techniques are required for single cell studies in order to gain new insights and understanding of cells' functions. The objective of my Ph.D. study was to fabricate, characterize, and apply submicrometric fluorescence sensors for the analysis of neuron cells. This dissertation will report the fabrication of miniaturized fluorescence sensors for Ca2+, pH and Zn2+ analysis. In the first approach, liposomes (phospholipid vesicles) were used as miniaturized containers for fluorescent sensing reagents. Liposome-based fluorescence sensing technology offers several advantages over commonly used fluorescence sensing techniques including high spatial resolution, protection of the sensing dye from quenchers and high biocompatibility. However, liposome based sensors were found to be unstable in the cellular environment. The second approach was to synthesize submicrometric particle-based fluorescence sensors named lipobeads to replace the fluorescent liposomes in cellular studies. Lipobeads are polystyrene particles that are coated with a phospholipid membrane. One unique advantage of fluorescent sensing lipobeads is the ability to immobilize hydrophobic indicator molecules in the phospholipid membrane. This enables the use of these indicators in aqueous media since the lipobeads are fully water miscible. The lipobeads also proved to be highly biocompatible in cellular studies. This is attributed to their phospholipid bilayer membrane, which is similar in structure to cell membranes. The dissertation will describe the analytical properties of fluorescence sensing lipobeads and their application in studying zinc ion release and pH changes near neuron cells under physiological conditions, conditions of neuronal injury and stress and acidic cortical spreading depression during stroke like conditions.
237

In Vitro Binding Kinetics of ChemoFilter with Cisplatin

Fisher, Joshua 26 October 2016 (has links)
<p> <b>Introduction:</b> Endovascular chemotherapy treatment allows localized delivery adjacent to the target tumor; allowing an increased dosage and decreased leakage to other areas. It also allows for the opportunity to filter chemotherapy escaping the target tumor and entering the bloodstream. The ChemoFilter - a temporarily deployable, endovascular device will do just that; reducing systemic toxicity thus reducing adverse side effects from chemotherapy treatment. This will allow further increased dosage, increased tumor suppression, and increased tolerance to treatment. ChemoFilter has successfully filtered the chemotherapeutic Doxorubicin, but had yet to be tested in other chemotherapeutics. This study evaluates binding with new chemotherapeutics: Cisplatin, Carboplatin, and a cocktail comprised of Cisplatin and Doxorubicin.</p><p> <b>Materials and Methods:</b> ChemoFilter prototypes based on: 1.) Genomic DNA and 2.) Dowex (ion-exchange) resin, were evaluated for their ability to bind chemotherapy in vitro in phosphate-buffered saline (PBS). ChemoFilter was tested free in solution and encapsulated in nylon or polyester mesh packets of various dimensions. Concentrations were quantified using inductively coupled plasma mass spectrometry (IPC-MS), ultraviolet-visible spectrophotometry (UV-Vis), or fluorospectrometry. <sup>11</sup>C, <sup>13</sup>C, and/or <sup> 14</sup>C radiolabeling Carboplatin began for in vitro and in vivo ChemoFilter quantification. In vitro quantification can include scintillation and/or gamma counting. In vivo may include Positron Emission Tomography (PET) imaging, Hyperpolarized <sup>13</sup>C Magnetic Resonance Imaging (MRI), and/or Magnetic Resonance Spectroscopy (MRS) for real-time visualization. Reactions were verified using High Performance Liquid Chromatography (HPLC) for chemical species identification.</p><p> <b>Results and Discussion:</b> Results indicate significant and nearly complete, ~99% (p&lt;0.01) clearance of Cisplatin using the DNA ChemoFilter sequestered in Nylon mesh, quantified with gold standard ICP-MS (evidenced at 214 and 265 nm). The Ion-exchange ChemoFilter has significant clearance, within seconds, of both Doxorubicin and Cisplatin mixed in a cocktail solution. However, it appears some Cisplatin is binding to the Nylon Mesh itself. Size, shape, and material of the mesh have been optimized. A potential mechanism for <sup>11</sup>C, <sup>13</sup>C, or <sup>14</sup>C radiolabeling of Carboplatin has been developed and early results have been successful. ChemoFilter works much more efficiently when sequestered in nylon packets of specific geometries. Significant improvements have been made to ChemoFilter, moving the device closer to clinical trials.</p>
238

Interactive 3D GPU-Based Breast Mass Lesion Segmentation Method Based on Level Sets for Dce-MRI Images

Unknown Date (has links)
A new method for the segmentation of 3D breast lesions in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) images, using parallel programming with general purpose computing on graphics processing units (GPGPUs), is proposed. The method has two main parts: a pre-processing step and a segmentation algorithm. In the pre-processing step, DCE-MRI images are registered using an intensity-based rigid transformation algorithm based on gradient descent. After the registration, voxels that correspond to breast lesions are enhanced using the Naïve Bayes machine learning classifier. This classifier is trained to identify four different classes inside breast images: lesion, normal tissue, chest and background. Training is performed by manually selecting 150 voxels for each of the four classes from images in which breast lesions have been confirmed by an expert in the field. Thirteen attributes obtained from the kinetic curves of the selected voxels are later used to train the classifier. Finally, the classifier is used to increase the intensity values of voxels labeled as lesions and to decrease the intensities of all other voxels. The post-processed images are used for volume segmentation of the breast lesions using a level set method based on the active contours without edges (ACWE) algorithm. The segmentation algorithm is implemented in OpenCL for the GPGPUs to accelerate the original model by parallelizing two main steps of the segmentation process: the computation of the signed distance function (SDF) and the evolution of the segmented curve. The proposed framework uses OpenGL to display the segmented volume in real time, allowing the physician to obtain immediate feedback on the current segmentation progress. The proposed implementation of the SDF is compared with an optimal implementation developed in Matlab and achieves speedups of 25 and 12 for 2D and 3D images, respectively. Moreover, the OpenCL implementation of the segmentation algorithm is compared with an optimal implementation of the narrow-band ACWE algorithm. Peak speedups of 55 and 40 are obtained for 2D and 3D images, respectively. The segmentation algorithm has been developed as open source software, with different versions for 2D and 3D images, and can be used in different areas of medical imaging as well as in areas within computer vision, such like tracking, robotics and navigation. / A Dissertation submitted to the Department of Scientific Computing in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2015. / November 2, 2015. / GPU, Level Sets, OpenCL, OpenGL, Segmentation / Includes bibliographical references. / Anke Meyer-Baese, Professor Directing Dissertation; Mark Sussman, University Representative; Gordon Erlebacher, Committee Member; Dennis Slice, Committee Member; Xiaoqiang Wang, Committee Member.
239

Pattern Recognition in Medical Imaging: Supervised Learning of fMRI and MRI Data

Unknown Date (has links)
Machine learning algorithms along with magnetic resonance imaging (MRI) provides promising techniques to overcome the drawbacks of the current clinical screening techniques. In this study the resting-state functional magnetic resonance imaging (fMRI) to see the level of activity in a patient's brain and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to explore the level of improvement of neo-adjuvant chemotherapy in patients with locally advanced breast cancer were considered. As the first project, we considered fMRI of patients before and after they underwent a double-blind smoking cessation treatment. For the first time, this study aims at developing new theory-driven biomarkers by implementing and evaluating novel techniques from resting-state scans that can be used in relapse prediction in nicotine-dependent patients and future treatment efficacy. In this regards, two classes of patients have been studied, one took the drug N-acetylcysteine and the other took a placebo. Our goal was to classify the patients as treatment or non-treatment, based on their fMRI scans. The image slices of brain are used as the variable. We have applied different voxel selection schemes and data reduction algorithms on all images. Then, we compared several multivariate classifiers and deep learning algorithms and also investigated how the different data reductions affect classification performance. For the second part, we have employed multi-parametric magnetic resonance imaging (mpMRI) using different morphological and functional MRI parameters such as T2-weighted, dynamic contrast-enhanced (DCE) MRI, and diffusion weighted imaging (DWI) has emerged as the method of choice for the early response assessments to NAC. Although, mpMRI is superior to conventional mammography for predicting treatment response, and evaluating residual disease, yet there is still room for improvement. In the past decade, the field of medical imaging analysis has grown exponentially, with an increased numbers of pattern recognition tools, and an increase in data sizes. These advances have heralded the field of radiomics. Radiomics allows the high-throughput extraction of the quantitative features that result in the conversion of images into mineable data, and the subsequent analysis of the data for an improved decision support with response monitoring during NAC being no exception. In this study. we determined the importance and ranking of the extracted parameters from mpMRI using T2-weighted, DCE, and DWI for prediction of pCR and patient outcomes with respect to metastases and disease-specific death employing different machine learning algorithms. / A Dissertation submitted to the Department of Scientific Computing in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / July 6, 2018. / Breast Cancer, Data Mining, Machine Learning, Medical Imaging, Neuroimaging / Includes bibliographical references. / Anke Meyer-Baese, Professor Directing Dissertation; Simon Y. Foo, University Representative; Katja Pinker-Domenig, Committee Member; Peter Beerli, Committee Member; Dennis Slice, Committee Member.
240

Towards the development of flexible, reliable, reconfigurable, and high-performance imaging systems

Khalifat, Jalal Mohamed January 2016 (has links)
Current FPGAs can implement large systems because of the high density of reconfigurable logic resources in a single chip. FPGAs are comprehensive devices that combine flexibility and high performance in the same platform compared to other platform such as General-Purpose Processors (GPPs) and Application Specific Integrated Circuits (ASICs). The flexibility of modern FPGAs is further enhanced by introducing Dynamic Partial Reconfiguration (DPR) feature, which allows for changing the functionality of part of the system while other parts are functioning. FPGAs became an important platform for digital image processing applications because of the aforementioned features. They can fulfil the need of efficient and flexible platforms that execute imaging tasks efficiently as well as the reliably with low power, high performance and high flexibility. The use of FPGAs as accelerators for image processing outperforms most of the current solutions. Current FPGA solutions can to load part of the imaging application that needs high computational power on dedicated reconfigurable hardware accelerators while other parts are working on the traditional solution to increase the system performance. Moreover, the use of the DPR feature enhances the flexibility of image processing further by swapping accelerators in and out at run-time. The use of fault mitigation techniques in FPGAs enables imaging applications to operate in harsh environments following the fact that FPGAs are sensitive to radiation and extreme conditions. The aim of this thesis is to present a platform for efficient implementations of imaging tasks. The research uses FPGAs as the key component of this platform and uses the concept of DPR to increase the performance, flexibility, to reduce the power dissipation and to expand the cycle of possible imaging applications. In this context, it proposes the use of FPGAs to accelerate the Image Processing Pipeline (IPP) stages, the core part of most imaging devices. The thesis has a number of novel concepts. The first novel concept is the use of FPGA hardware environment and DPR feature to increase the parallelism and achieve high flexibility. The concept also increases the performance and reduces the power consumption and area utilisation. Based on this concept, the following implementations are presented in this thesis: An implementation of Adams Hamilton Demosaicing algorithm for camera colour interpolation, which exploits the FPGA parallelism to outperform other equivalents. In addition, an implementation of Automatic White Balance (AWB), another IPP stage that employs DPR feature to prove the mentioned novelty aspects. Another novel concept in this thesis is presented in chapter 6, which uses DPR feature to develop a novel flexible imaging system that requires less logic and can be implemented in small FPGAs. The system can be employed as a template for any imaging application with no limitation. Moreover, discussed in this thesis is a novel reliable version of the imaging system that adopts novel techniques including scrubbing, Built-In Self Test (BIST), and Triple Modular Redundancy (TMR) to detect and correct errors using the Internal Configuration Access Port (ICAP) primitive. These techniques exploit the datapath-based nature of the implemented imaging system to improve the system's overall reliability. The thesis presents a proposal for integrating the imaging system with the Robust Reliable Reconfigurable Real-Time Heterogeneous Operating System (R4THOS) to get the best out of the system. The proposal shows the suitability of the proposed DPR imaging system to be used as part of the core system of autonomous cars because of its unbounded flexibility. These novel works are presented in a number of publications as shown in section 1.3 later in this thesis.

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