The registration of pre-operative volumetric datasets to intra- operative two-dimensional images provides an improved way of verifying patient position and medical instrument loca- tion. In applications from orthopedics to neurosurgery, it has a great value in maintaining up-to-date information about changes due to intervention. We propose a mutual information- based registration algorithm to establish the proper align- ment. For optimization purposes, we compare the perfor- mance of the non-gradient Powell method and two slightly di erent versions of a stochastic gradient ascent strategy: one using a sparsely sampled histogramming approach and the other Parzen windowing to carry out probability density approximation. Our main contribution lies in adopting the stochastic ap- proximation scheme successfully applied in 3D-3D registra- tion problems to the 2D-3D scenario, which obviates the need for the generation of full DRRs at each iteration of pose op- timization. This facilitates a considerable savings in compu- tation expense. We also introduce a new probability density estimator for image intensities via sparse histogramming, de- rive gradient estimates for the density measures required by the maximization procedure and introduce the framework for a multiresolution strategy to the problem. Registration results are presented on uoroscopy and CT datasets of a plastic pelvis and a real skull, and on a high-resolution CT- derived simulated dataset of a real skull, a plastic skull, a plastic pelvis and a plastic lumbar spine segment.

Accurate insertion and monitoring of metal implants in-vivo is essential for clinical diagnosis and therapy of various diseases. Clinical studies and examples have demonstrated that the misplacement errors of these metal devices can have dramatic consequences. This thesis focuses on three main metal devices that are in widespread use today: needles, coronary stents and brachytherapy seeds. Each application requires proper image-guidance for correct usage. For needles, image guidance is required to ensure correct local injection delivery or needle aspiration biopsy. Fine needle aspiration biopsies are performed in order to avoid major surgical excisions when obtaining tissue biopsy procedures. However, because of the small biopsy sample, the risk is that the sample is collected outside of the tumorigenic region, resulting in a false negative result. Implantation of stents requires that confirmation that proper stent apposition has been achieved due to balloon inflation. Furthermore, it is important to guide the stent to shield the vulnerable region of an atherosclerotic plaque. With prostate brachytherapy seeds, the ability to monitor seed placement is crucial because needle deflections or tissue deformation can result in seed misplacement errors, decreasing the efficacy of the pre-established treatment plan. For the described applications and other possible clinical practices involving the use of metallic implants, an imaging technology that can accurately depict the location of the metal objects, relative to their respective backgrounds, in real-time, is necessary to improve the safety and the efficacy of these procedures. Currently, ultrasound is used because of its real-time capabilities, non-ionizing radiation, and soft tissue contrast. However, due to high acoustic scattering from tissue, the contrast of metal implants can be low. Photoacoustic imaging can be used as an alternative, or complementary, imaging method to ultrasound for imaging metal. This thesis focuses on the benefits and the pitfalls of using photoacoustic imaging for detecting three different metal implants, each having unique requirements. Overall, the goal of this work is to develop a framework for clinical applications using combined ultrasound and photoacoustic imaging to help guide, detect and follow-up on clinical metal implants introduced in-vivo. / text

<p> The emergence of more sophisticated full body plethysmograph systems has occurred over recent years and called for broader testing of respiratory functions. Specific airway resistance and intrathoracic gas volume or functional residual capacity can provide more accurate measure of lung function utilizing a computerized full body plethysmograph. Clinics or specialized test facilities today could use this type of system for testing, evaluation, and long term monitoring of patients suspected of suffering from pulmonary disease of which there is no cure. A virtual machine was used for pulmonary function test and serialized collaboration of data was demonstrated to offer more access to diagnosis and treatment of respiratory diseases. Another non-invasive method of respiratory function can be indirectly measured from electrocardiogram. In addition patient respiratory rate is routinely measured using acoustic method. This multiphase evaluation of respiratory function examined cloud services, virtual machines, spirometry, plethysmography, indirect, and acoustic assessment of pulmonary function.</p>

<p> This study uses ultrasound to image onset velar stop consonant articulation in words. By examining tongue body placement, the extent of velar closure variation across vowel contexts provides for the measurement of anticipatory coarticulation while productions within the same vowel context provide measurement of extent of token-to-token variation. Articulate Assistant Advanced 2.0 software was used to semi-automatically generate midsagittal tongue contours at the initial point of maximum velar closure and was used to fit each contour to a curved spline. Patterns of lingual coarticulation and measures of speech motor stability, based on curve-to-curve distance (Zharkova, Hewlett, &amp; Hardcastle, 2011), are investigated to compare the speech of typically fluent speakers to the speech of people who stutter. Anticipatory coarticulation can be interpreted as a quantitative measure indicating the maturity of the speech motor system and its planning abilities. Token-to-token variability is examined from multiple velar vowel productions within the same vowel context, describing the accuracy of control, or stability, of velar closure gestures. Measures for both speaking groups are examined across the lifespan at stages during speech development, maturation, and aging. Results indicate an overall age effect, interpreted as refinement, with increased speech stability and progressively more segmental (less coarticulated) productions across the lifespan. A tendency toward decreased stability and more coarticulated speech was found for younger people who stutter, but this difference was small and absent among older adults. Outcomes of this study suggest the articulatory maturation trajectories of people who stutter may be delayed, but overall maturation of the speech mechanism is evident by older adulthood for typically fluent speakers and those who stutter. Applications to intervention are discussed in closing. </p>

<p> Central nervous system (CNS) related conditions and diseases like mild traumatic brain injury (mTBI) and multiple sclerosis (MS) affect people&rsquo;s life quality, yet there is no single test for the diagnosis of these diseases or conditions. Patients may need to wait for years until they are diagnosed correctly to get the correct treatment, which is often too late. Thus, there is a strong need to develop some techniques to aid the diagnosis of CNS-related conditions and diseases. The conventional MRI can reveal the structure of the brain but cannot detect the difference between the healthy tissue and the anomalies. Diffusion tensor imaging (DTI) has been used for detecting white matter integrity and demyelination for the past decade in experiments and has been proven to have the ability to depict the problem effectively. In the past decade, many techniques were found based on DTI data, and these techniques improved pre-processing, processing, and post-processing. </p><p> Though there are many software and APIs that can provide functions for DTI file input/output (IO), visualization and other DTI related topics, there is no general software or API that is dedicated to covering the whole processing procedure of DTI that at the same time can be extended easily by the user. This thesis is dedicated to developing a software that can be used to aid in the diagnosis of CNS-related conditions and diseases while at the same time trying to cover as many topics as possible. Another purpose is to make the software highly extensible. </p><p> This thesis work first introduces the background of CNS-related disease and uses MS as an example to introduce the process of demyelination and the white matter integrity problem, which are involved in these CNS-related diseases and conditions. Then the diffusion process and the technique that can detect the diffusion signal (DTI) is presented. After this, concepts and meaning of the secondary metrics are discussed. Then, current existing software and APIs and their advantages and disadvantages are outlined. After these points, the techniques that are discussed in this thesis as well as their advantages are outlined. This part is followed by the charts and code samples which can illustrate the process and structure of this software. Then different modules and their results are explained. </p><p> In this software, the results are represented by images and 3D models. There are color images, pseudo color images with different schemes and gray scale images. Images are mainly included to represent the FA and MD data. In this software, streamlines are generated from the eigenvalue and eigenvector. Then a bundled result for the streamline is also realized in this software. The streamline and bundled results are 3D models. For 3D models, there are mainly two ways to display the real 3D model. One is the naked eye 3D which doesn&rsquo;t require the user to wear glasses but has less stereoscopic characteristics. As the stereoscopic monitors and glasses are more and more popular and easily accessible, this software also provides stereoscopic views for 3D models, and the user can choose red &amp; blue, interlaced techniques with proper glasses. </p><p> This thesis work ends with the discussion of the results and limitations of DTI. Finally, there is a discussion about the future work that can improve the performance of this software and topics that need to be covered.</p>

<p> <i>Background:</i> Post-traumatic stress disorder (PTSD) is a mental health disorder characterized by symptoms such as insomnia, irritability, issues with memory, difficulty concentrating, and poor decision-making abilities. With symptoms that closely resemble those of other anxiety disorders, it is very difficult to accurately diagnose. More research is needed to identify structural and functional imaging biomarkers to aid in diagnosis.</p><p> <i>Methods:</i> Ten right-handed male subjects (5 combat-exposed veterans, 5 healthy civilian controls) underwent magnetoencephalographic recording for this study. MEG data were acquired with a 275-channel whole-head CTF Omega 2000 system. Resting-state and tasked-based (Stroop Color-Naming Task) data were acquired. Voxel-based time-frequency analysis was subsequently performed using NUTMEG and SPM8.</p><p> <i>Results:</i> Significant differences were found between the two groups at rest (in delta, theta, gamma, and high-gamma neural oscillatory frequency bands) and during the Stroop Color-Naming task (in alpha, beta, and gamma, and high-gamma frequency bands).</p><p> <i>Conclusions:</i> Despite the small sample size, we were able to replicate some aspects of previous MEG research in veterans with PTSD. Not only does this result substantiate the use of MEG for population studies, but it also shows that PTSD is a mental disorder that is physical in nature and can be characterized through passively observing electromagnetic neuronal activity.</p>

Treatment response assessment in advanced head and neck cancer patients using Positron Emission Tomography (PET) has potential to provide significant clinical benefit. PET quantification methods can be either static or dynamic. The static approach is simple and is widely used. The simplified dynamic PET quantification method is a promising approach as it provides a reasonable trade-off between accuracy and clinical practicality. This method requires a blood sample which makes it not ideal since the PET quantification accuracy may be compromised due to small activity and volume of the blood sample. The implementation of image-based simplified dynamic PET quantification in head and neck cancer patients requires partial volume correction due to small vessel sizes and limitted PET spatial resolution. The objective of this thesis is to evaluate the accuracy of current PET quantification methods for response assessment in advanced head and neck cancer patients and to develop a novel and robust partial volume correction technique to improve PET quantification. First, the static PET quantification method using fixed size ROI is evaluated. Significant variation in response assessment was observed suggesting that static PET quantification using a fixed-size ROI should be approached with caution in heterogeneous tumours. Second, the accuracy of blood activity measurements and its effect on the accuracy of quantitative response assessment is evaluated. Significant inaccuracies in the blood sample based simplified dynamic PET quantification method are identified. The results support a need to develop an image-based simplified dynamic PET quantification method with partial volume correction. Finally, a novel partial volume correction technique was developed, validated, and its robustness was investigated. In comparison to previously published partial volume correction techniques, it performed better with noisy PET images and it was more robust for errors in PET-CT registration. The partial volume correction technique was also implemented and validated in sinogram space to provide additional advantages such as applicability to iterative reconstructions. The proposed partial volume correction technique enables the use of image-based simplified dynamic PET quantification in advanced head and neck cancer patients. Furthermore, the technique establishes a framework for future research to address the inherent low spatial resolution of PET.

Treatment response assessment in advanced head and neck cancer patients using Positron Emission Tomography (PET) has potential to provide significant clinical benefit. PET quantification methods can be either static or dynamic. The static approach is simple and is widely used. The simplified dynamic PET quantification method is a promising approach as it provides a reasonable trade-off between accuracy and clinical practicality. This method requires a blood sample which makes it not ideal since the PET quantification accuracy may be compromised due to small activity and volume of the blood sample. The implementation of image-based simplified dynamic PET quantification in head and neck cancer patients requires partial volume correction due to small vessel sizes and limitted PET spatial resolution. The objective of this thesis is to evaluate the accuracy of current PET quantification methods for response assessment in advanced head and neck cancer patients and to develop a novel and robust partial volume correction technique to improve PET quantification. First, the static PET quantification method using fixed size ROI is evaluated. Significant variation in response assessment was observed suggesting that static PET quantification using a fixed-size ROI should be approached with caution in heterogeneous tumours. Second, the accuracy of blood activity measurements and its effect on the accuracy of quantitative response assessment is evaluated. Significant inaccuracies in the blood sample based simplified dynamic PET quantification method are identified. The results support a need to develop an image-based simplified dynamic PET quantification method with partial volume correction. Finally, a novel partial volume correction technique was developed, validated, and its robustness was investigated. In comparison to previously published partial volume correction techniques, it performed better with noisy PET images and it was more robust for errors in PET-CT registration. The partial volume correction technique was also implemented and validated in sinogram space to provide additional advantages such as applicability to iterative reconstructions. The proposed partial volume correction technique enables the use of image-based simplified dynamic PET quantification in advanced head and neck cancer patients. Furthermore, the technique establishes a framework for future research to address the inherent low spatial resolution of PET.

Field Cycled Magnetic Resonance Imaging offers potential for significant Signal to Noise Ratio and T₁ contrast improvements of Magnetic Resonance images. In this work the hardware and software components of a home made, low field NMR imager were modified, in order to investigate Field Cycling. Theoretical models were developed to simulate NMR signal response to different magnetic field pulse shapes and it was seen that trapezoidal magnetic field pulse waveforms, with rise/fall times considerably smaller than the T₁ relaxation times of the examined samples, give comparable results to those of an ideal, rectangular pulse. The steady state signal expressions of Field Cycled Gradient Echo and Spin Echo sequences were derived and tested experimentally. Differences between theoretical and experimental results can be attributed to the increased levels of noise and the effect of time dependent magnetic fields due to limited efficiency of the induced current cancelling scheme. The ability of the imager to measure T₁ relaxation times at different magnetic field strengths, employing Field Cycled imaging sequences, was also assessed. Results were again burdened by the above mentioned problems, as well as, by the considerable temperature changes the samples suffered during the long imaging times required for complete study.

<p>Dynamic contrast-enhanced (DCE) MRI has been widely used as a quantitative imaging method for monitoring tumor response to therapy. The pharmacokinetic parameters derived from this technique have been used in more than 100 phase I trials and investigator led studies. The simultaneous challenges of increasing the temporal and spatial resolution, in a setting where the signal from the much smaller voxel is weaker, have made this MR technique difficult to implement in small-animal imaging. Existing preclinical DCE-MRI protocols acquire a limited number of slices resulting in potentially lost information in the third dimension. Furthermore, drug efficacy studies measuring the effect of an anti-angiogenic treatment, often compare the derived biomarkers on manually selected tumor regions or over the entire volume. These measurements include domains where the interpretation of the biomarkers may be unclear (such as in necrotic areas).</p><p>This dissertation describes and compares a family of four-dimensional (3D spatial + time), projection acquisition, keyhole-sampling strategies that support high spatial and temporal resolution. An interleaved 3D radial trajectory with a quasi-uniform distribution of points in k-space was used for sampling temporally resolved datasets. These volumes were reconstructed with three different k-space filters encompassing a range of possible keyhole strategies. The effect of k-space filtering on spatial and temporal resolution was studied in phantoms and in vivo. The statistical variation of the DCE-MRI measurement is analyzed by considering the fundamental sources of error in the MR signal intensity acquired with the spoiled gradient-echo (SPGR) pulse sequence. Finally, the technique was applied for measuring the extent of the opening of the blood-brain barrier in a mouse model of pediatric glioma and for identifying regions of therapeutic effect in a model of colorectal adenocarcinoma. </p><p>It is shown that 4D radial keyhole imaging does not degrade the system spatial and temporal resolution at a cost of 20-40% decrease in SNR. The time-dependent concentration of the contrast agent measured in vivo is within the theoretically predicted limits. The uncertainty in measuring the pharmacokinetic parameters with the sequences is of the same order, but always higher than, the uncertainty in measuring the pre-injection longitudinal relaxation time. The histogram of the time-to-peak provides useful knowledge about the spatial distribution of K^trans and microvascular density. Two regions with distinct kinetic parameters were identified when the TTP map from DCE-MRM was thresholded at 1000 sec. The effect of bevacizumab, as measured by a decrease in K^trans, was confined to one of these regions. DCE-MRI studies may contribute unique insights into the response of the tumor microenvironment to therapy.</p> / Dissertation