Positron Emission Tomography (PET) is an imaging modality that has become increasingly beneficial in Radiotherapy by improving treatment planning (1). PET reveals tumor volumes that are not well visualized on computed tomography CT or MRI, recognizes metastatic disease, and assesses radiotherapy treatment (1). It also reveals areas of the tumor that are more radiosensitive allowing for dose painting - a non-homogenous dose treatment across the tumor (1). However, PET is not without limitations. The quantitative unit of PET images, the Standardized Uptake Value (SUV), is affected by many factors such as reconstruction algorithm, patient weight, and tracer uptake time (2). In fact, PET is so sensitive that a patient imaged twice in a single day on the same machine and same protocol will produce different SUV values. The objective of this research was to increase the capabilities of PET by exploring other quantitative PET/CT measures for Radiotherapy treatment applications. The technique of quantitative image feature analysis, nowadays known as radiomics, was applied to PET and CT images. Image features were then extracted from PET/CT images and how the features differed between conventional and respiratory-gated PET/CT images in lung cancer was analyzed. The influence of noise on image features was analyzed by applying uncorrelated, Gaussian noise to PET/CT images and measuring how significantly noise affected features. Quantitative PET/CT measures outside of image feature analysis were also investigated. The correlation of esophageal metabolic tumor volumes (tumor volume demonstrating high metabolic uptake) and endoscopically implanted fiducial markers was studied. It was found that certain image features differed greatly between conventional and respiratory-gated PET/CT. The differences were mainly due to the effect of respiratory motion including affine motion, rotational motion and tumor deformation. Also, certain feature groups were more affected by noise than others. For instance, contour-dependent shape features exhibited the least change with noise. Comparatively, GLSZM features exhibited the greatest change with added noise. Discordance was discovered between the inferior and superior tumor fiducial markers and metabolic tumor volume (MTV). This demonstrated a need for both fiducial markers and MTV to provide a comprehensive view of a tumor. These studies called attention to the differences in features caused by factors such as motion, acquisition parameters, and noise, etc. Investigators should be aware of these effects. PET/CT radiomic features are indeed highly affected by noise and motion. For accurate clinical use, these effects must be account by investigators and future clinical users. Further investigation is warranted towards the standardization of PET/CT radiomic feature acquisition and clinical application.

Heart failure is a common condition during which the pumping action of the heart is affected because the heart does not contract or relax properly. Heart failure affects about 5 million Americans, with 550,000 new cases diagnosed each year. Cardiac resynchronization therapy (CRT) is used to treat symptoms and other complications associated with a heart failure. While performing CRT, Implantation of a pacing lead in the left ventricle of the heart is a very challenging surgical procedure performed with fluoroscopy. The target location is often difficult to reach through the tortuous coronary venous anatomy, which varies greatly among individuals. Placement of the pacing lead is an important research topic because the ideal pacing location for some patients with heart disease may be the site of latest contraction in the left ventricle. The purpose of this project is to develop an algorithm to locate and track points on a lead in a sequence of images. The algorithm will track the motion of the points over time and generate displacement plots over time.

<p>Small animal imaging is a valuable tool in preclinical biomedical research which relies on the use of animal models to understand human disease. Newly emerging optical imaging techniques such as bioluminescence tomography offer an inexpensive and sensitive alternative to more established imaging technologies. These techniques are capable of non-invasively imaging a variety of cellular and molecular processes <em>in vivo</em>. As an emerging technology, current bioluminescence imaging methods suffer from several limitations, preventing them from reaching their full potential.</p> <p>In this work, we describe the design and characterization of an integrated imaging system capable of multispectral bioluminescence tomography (BLT), diffuse optical tomography (DOT), and X-ray computed tomography (CT). The system addresses many of the inherent problems encountered in planar bioluminescence imaging techniques, allowing for the recovery of more accurate and quantitative bioluminescence data. The integrated X-ray CT scanner provides anatomical information which aids in the visualization and localization of the recovered bioluminescence distributions and also helps to constrain the inverse reconstruction in the diffuse optical tomography system. It was found that the inclusion of spatial priors from X-ray CT improved the reconstructed image quality dramatically. Four image reconstruction algorithms were evaluated for their ability to recover the effective attenuation coefficients of a series of test phantoms. Two of the algorithms (a modified Levenberg-Marquardt method, and a single-step Tikhonov method) did not use any <em>a priori</em> spatial information. Two other algorithms (hard priors and soft priors) used <em>a priori </em>structural information from X-ray CT to constrain the reconstruction process. The two methods incorporating spatial prior information resulted in recovered optical property distributions with RMS errors ranging from 8 % to 15 % in a series of test phantoms versus errors of 11 % to 26 % for non-spatial methods. The soft priors method was shown to be more resilient to imperfect <em>a priori</em> information.</p> <p>The multispectral BLT component was used to recover accurate bioluminescence distributions in test phantoms using <em>a priori</em> background optical properties recovered from the DOT system. Multispectral measurements were shown to provide an accurate method for estimating the position of a bioluminescence source due to the wavelength dependent attenuation of tissue. Experimental measurements are presented which explore the importance of accurate estimates of background optical properties in BLT. The hard spatial prior method was found to provide the best overall recovery of total source strength, position, and fidelity at all source depths up to 12.5 mm. The total source strength was recovered to within 8 %, while the source position was recovered to within 0.16 mm in all cases. Errors in recovered power and position showed no dependence on depth up to the maximum of 12.5 mm.</p> / Doctor of Philosophy (PhD)

<p>In this thesis, inverse problems related to microwave imaging and microwave component design are investigated. Our contribution in microwave imaging for breast tumor detection can be divided into two parts. In the first part, a vectorial 3D near-field microwave holography is proposed which is an improvement over the existing holography algorithms. In the second part, a simple and fast post-processing algorithm based on the principle of blind de-convolution is proposed for removing the integration effect of the antenna aperture. This allows for the data collected by the antennas to be used in 3D holography reconstruction. The blind deconvolution algorithm is a well-known algorithm in signal processing and our contribution here is its adaptation to microwave data processing.</p> <p>Second, a procedure for accelerating the space-mapping optimization process is presented. By exploiting both fine- and surrogate-model sensitivity information, a good mapping between the two model spaces is efficiently obtained. This results in a significant speed-up over direct gradient-based optimization of the original fine model and enhanced performance compared with other space-mapping approaches. Our approach utilizes commercially available software with adjoint-sensitivity analysis capabilities.</p> / Thesis / Master of Applied Science (MASc)

<p>In this thesis we consider the need to generate efficient solvers for inverse imaging problems in a way that supports both quality and performance in software, as well as flexibility in the underlying mathematical models. Many problem domains involve large data sizes and rates, and changes in mathematical modelling are limited only by researcher ingenuity and driven by the value of the application. We use a problem in Magnetic Resonance Imaging to illustrate this situation, motivate the need for better software tools and test the tools we develop. The problem is the determination of velocity profiles, think blood-flow patterns, using Phase Contrast Angiography. Despite the name, this method is completely noninvasive, not requiring the injection of contrast agents, but it is too time-consuming with present imaging and computing technology.</p> <p>Our approach is to separate the specification, the mathematical model, from the implementation details required for performance, using a custom language. The Domain Specific Language (DSL) provided to scientists allows for a complete abstraction from the highly optimized generated code. The mathematical DSL is converted to an internal representation we refer to as the Coconut Expression Library. Our expression library uses the directed acyclic graphs as an underlying data structure, which lends itself nicely to our automatic simplifications, differentiation and subexpression elimination. We show how parallelization and other optimizations are encoded as rules which are applied automatically rather than schemes that need to be implemented by the programmer in the low-level implementation. Finally, we present results, both in terms of numerical results and computational performance.</p> / Master of Science (MSc)

<p>MR phase images contain essential information about local magnetic susceptibility sources in the brain, creating a new type of contrast in magnetic resonance imaging (MRI). The goal of this thesis is to demonstrate with a model of the brain how accurately the transformation of phase to susceptibility takes place.</p> <p>A 3D brain model uses the Forward process to calculate magnetic field perturbations caused by susceptibility properties of the tissues in the model. Homodyne High Pass (HP) filter and SHARP algorithm are used to process the simulated phase images. Similarly, MR magnitude data are simulated using tissue properties such as T₁, T₂^* relaxation times and spin density.</p> <p>The halo ring around red nucleus in the real phase data is believed to be an indicator of a capsule around red nucleus. Similar effect is seen in the simulated phase images without including the capsule of red nucleus in the model, this comparison explains that the halo effect may just be entirely or a part of the phase behavior around red nucleus. A negative susceptibility in the internal capsule region, seen in both simulated and real susceptibility maps, is discussed as a possible artifact caused by the processing techniques after comparing the simulated susceptibility maps produced from unprocessed and processed phase data. The brain model is used to determine the optimum echo time of the initial gradient echo sequence in order to produce a high quality susceptibility map with reasonably low error and better time efficiency.</p> / Master of Applied Science (MASc)

<p>This thesis provides new regression methods for the removal of structured noise in datasets. With multivariable data, the variables and the noise can be both temporally correlated (i.e. auto correlated in time) and contemporaneously correlated (i.e. cross-correlated at the same time). In many occasions it is possible to acquire measurements of the noise, or some function of it, during the data collection. Several new constrained latent variable methods (LVM) that are built upon previous LVM regression frameworks are introduced. These methods make use of the additional information available about the noise to decompose a dataset into basis for the noise and signal. The properties of these methods are investigated mathematically, and through both simulation and application to actual biomedical data.</p> <p>In Chapter Two, linear, constrained LVM methods are introduced. The performance of these methods are compared to the other similar LVM methods as well as ordinary PLS throughout several simulation studies. In Chapter Three, a NIPALS type algorithm is developed for the soft constrained PLS method which is also able to account for missing data as well as datasets with large covariance matrices. Chapter Four introduces the nonlinear-kernelized constrained LVM methods. These methods are capable of handling severe nonlinearities in the datasets. The performance of these methods are compared to nonlinear kernel PLS method. In Chapter Five the constrained methods are used to remove ballistocardiographic and muscle artifacts from EEG datasets in combined EEG-fMRI as well as single EEG experiments on patients. The results are shown and compared to the standard noise removal methods used in the field. Finally in Chapter Six, the overall conclusion and scope of the future work is laid out.</p> / Doctor of Philosophy (PhD)

<p>High-content screening (HCS) produces an immense amount of data, often on the scale of Terabytes. This requires considerable processing power resulting in long analysis time. As a result, HCS with a single-core processor system is an inefficient option because it takes a huge amount of time, storage and processing power. The situation is even worse because most of the image processing software is developed in high-level languages which make customization, flexibility and multi-processing features very challenging. Therefore, the goal of the project is to develop a multithreading model in C language. This model will be used to extract subcellular localization features, such as threshold adjacency statistics (TAS) from the HCS data. The first step of the research was to identify an appropriate dye for use in staining the MCF-7 cell line. The cell line has been treated with staurosporin kinase inhibitor, which can provide important physiological and morphological imaging information. The process of identifying a suitable dye involves treating cells with different dye options, capturing the fluorescent images of the treated cells with the Opera microscope, and analyzing the imaging properties of the stained cells. Several dyes were tested, and the most suitable dye to stain the cellular membrane was determined to be Di4-Anepps. The second part of the thesis was to design and develop a parallel program in C that can extract TAS features from the stained cellular images. The program reads the input cell images captured by Opera microscopes, converts it to TIFF format from the proprietary Opera format, identifies the region-of-interest contours of each cell, and computes the TAS features. A significant increase in speed in the order of four fold was obtained using the customized program. Different scalability tests using the developed software were compared against software developed in Acapella scripting language. The result of the test shows that the computational time is proportional to number of cells in the image and is inversely proportional to number of cores in a processor.</p> / Master of Applied Science (MASc)

<p>A microfluidic device capable of drug delivery to multiple wells in a concentration gradient was designed for automated high content and high throughput screening. The design was proposed to utilize a nanoporous polycarbonate membrane to spatially and temporally control drug dosage from the microchannels below to the wells above. Microchannels were to hold to the drugs or reagents, while wells were to culture cells. An array of 16 wells was to fit in the equivalent area of a single well of a 96 well plate. Two simpler devices were created to validate electrokinetic drug delivery to a single well and to characterize cell proliferation and viability in micro-wells. The first device tested drug delivery to a single well with methylene blue dye at applied voltages of 100V, 125V, and 150V. It was validated that the dosage of dye could be controlled by increasing the voltage and by increasing the duration the voltage was applied. The second devices were a series of 9-well arrays, each testing a different diameter (1.2 mm – 0.35 mm). These devices were cultured with MCF-7 breast cancer cells over 5 days. At the end of the 5 day study, all diameters except for 0.5 mm and 0.35 mm measured a cell viability of 99% and exhibited cell growth patterns similar to coverslip glass controls. The proposed integrated cell culture and drug delivery device could have application towards early stage drug discovery and could have compatibility with lab equipment originally designed for well plates.</p> / Master of Applied Science (MASc)

ACL injury has been shown to have long-lasting and severe consequences on the different structures of the knee such as the articular cartilage and meniscus. Cartilage thickness changes in particular are indicative of osteoarthritic changes in the tibiofemoral joint. While there has been significant research focused on cartilage changes of the tibia and femur, there has been little work looking at patellar cartilage. The following goals were set forth for this study. First, to establish a robust coordinate system to accurately determine the location and orientation of the patella. Secondly, to determine the effects of ACL injury on patellar cartilage thickness. Twenty-one individuals (10 males, 11 females) were studied. All individuals had suffered first time ACL injuries to one of their knees. MRI data from both the healthy and injured knees were collected an average of 4 ± 0.9 years. Using MRI data, the bone and cartilage surfaces were manually segmented and imported into MATLAB for study. Differences in cartilage thickness values between the healthy and unhealthy knees within individuals was the primary measure of analysis. Analysis revealed a total of 9 square millimeters of cartilage surface area that were statistically significant. Four square millimeters of significant difference were found in males in the medial superior compartment, (mean thickness difference = -0.381 mm, with SD = 0.084mm, indicating thinning). Five square millimeters of significant difference were found in females in the medial inferior compartment (mean thickness difference = 0.551 mm, SD = 0.015mm, indicating thickening). This suggests regional and sex related cartilage thickness changes occur following ACL injury, surgery, and 4 year follow-up.