A Positive Electron Tomography/Computed Tomography devise was installed in the X-ray section at US Linköping in May 2007. Positive Electron Tomography examinations with 18F-fluoro-deoxyglucose are mainly used for tumor examinations. During 2007 occurred approximately 200 examinations and in 2008 600 are planned.Today there are two reconstruction methods commercially available, Filtered Back projection and Maximum Likelihood Expectation Maximiza tion, used in the faster version called Ordered Subsets Expectation Maximization. The image quality in Positive Electron Tomography depends on the choice of reconstruction method and the settings of its parameters. We have performed a physical phantom study with Positive Electron Tomography to determine optimal parameters for the iterativereconstruction algorithm Ordered Subsets Expectation Maximization. To find out whether or not the quality of the image can be improved, so that the patient received radiation dose and/or examination time can be lowered. The phantom used was a NEMA IEC Body PhantomTM, designed to mimic small hot lesions typicalin 18F, Fluorine-18 PET, and all calculations were done according to the NEMA NU2-2001 protocol. The main conclusion from this project is that a higher level of contrastcan be reached, compared to the one clinically obtained today. Using more iterations then recommended from the manufacturer.

<p>In the United States, heart failure is a leading cause of hospitalization. The medical industry places great emphasis on diagnosing heart disease through cardiac metrics like ejection fraction. Left ventricular ejection fraction is a commonly used diagnostic indicator for heart efficiency and is measured with echocardiography through different volume calculation techniques. However, ejection fraction results can drastically vary from one examiner to another. Generally cardiologists still give ejection fraction measurements a plus or minus 10 percent error range. </p><p>A program developed at Duke called 4DViz is robust enough for users to process 3D ultrasound data. 4DViz allows examiners to determine heart chamber volumes by constructing a surface model over an imaged heart chamber with many mouse click inputs. Through 4DViz programming, a viable approach for calculating ejection fraction is attempted in this thesis. Using feature tracking, surface drawing, and voxel filling, the new approach aims to reduce examiner input and improve ejection fraction consistency. Water filled balloons were used to calibrate the algorithm's parameters. In testing, several volunteers were asked to use the 4DViz. Their results are compared to volume measurements where user input was standard. The results show promise and may remove some of the inconsistency behind ejection fraction measurements.</p> / Thesis

Cell count is an important metric in neurological research. The loss in numbers of certain cells like neurons has been found to accompany not only the deterioration of important brain functions but disorders like clinical depression as well. Since the manual counting of cell numbers is a near impossible task considering the sizes and numbers involved, an automated approach is the obvious alternative to arrive at the cell count. In this thesis, a software application is described that automatically segments, counts, and helps visualize the various cell bodies present in a sample mouse brain, by analyzing the images produced by the Knife-Edge Scanning Microscope (KESM) at the Brain Networks Laboratory. The process is described essentially in five stages: Image acquisition, Pre- Processing, Processing, Analysis and Refinement, and finally Visualization. Nissl staining is a staining mechanism that is used on the mouse brain sample to highlight the cell bodies of our interest present in the brain, namely neurons, granule cells and interneurons. This stained brain sample is embedded in solid plastic and imaged by the KESM, one section at a time. The volume that is digitized by this process is the data that is used for the purpose of segmentation. While most sections of the mouse brain tend to be comprised of sparsely populated neurons and red blood cells, certain sections near the cerebellum exhibit a very high density and population of smaller granule cells, which are hard to segment using simpler image segmentation techniques. The problem of the sparsely populated regions is tackled using a combination of connected component labeling and template matching, while the watershed algorithm is applied to the regions of very high density. Finally, the marching cubes algorithm is used to convert the volumetric data to a 3D polygonal representation. Barring a few initializations, the process goes ahead with minimal manual intervention. A graphical user interface is provided to the user to view the processed data in 2D or 3D. The interface offers the freedom of rotating and zooming in/out of the 3D model, as well as viewing only cells the user is interested in analyzing. The segmentation results achieved by our automated process are compared with those obtained by manual segmentation by an independent expert.

This research is primarily focused on laser-based non-invasive photoacoustic tomography of small animal brains. Photoacoustic tomography, a novel imaging modality, was applied to visualize the distribution of optical absorptions in small-animal brains through the skin and skull. This technique combines the high-contrast advantage of optical imaging with the high-resolution advantage of ultrasonic imaging. Based on the intrinsic optical contrast, this imaging system successfully visualized three-dimensional tissue structures in intact brains, including lesions and tumors in brain cerebral cortex. Physiological changes and functional activities in brains, including cerebral blood volume and blood oxygenation in addition to anatomical information, were also satisfactorily monitored. This technique successfully imaged the dynamic distributions of exogenous contrast agents in small-animal brains. Photoacoustic angiography in small-animal brains yielding high contrast and high spatial resolution was implemented noninvasively using intravenously injected absorbing dyes. In the appendix, the theory of Monte Carlo simulation of polarized light propagation in scattering media was briefly summarized.

We investigate the possibility of extracting accurate functional information such as local blood oxygenation level using multi-wavelength photoacoustic measurements. Photoacoustic microscope is utilized to acquire images of microvasculature in smallanimal skin. Owing to endogenous optical contrast, optical spectral information obtained from spectral photoacoustic measurements are successfully inverted to yield oxygenation level in blood. Analysis of error propagation from photoacoustic measurements to inverted quantities showed minimum inversion error in the optical wavelength region of 570-600 nm. To obtain accurate and vessel size independent blood oxygenation measurements, transducers with central frequency of more than 25 MHz are needed for the optical region of 570-600 nm used in this study. The effect of transducer focal position on accuracy of blood oxygenation level quantification was found to be negligible. To obtain accurate measurements in vivo, one needs to compensate for factors such as spectral dependent optical attenuation.

Cell count is an important metric in neurological research. The loss in numbers of certain cells like neurons has been found to accompany not only the deterioration of important brain functions but disorders like clinical depression as well. Since the manual counting of cell numbers is a near impossible task considering the sizes and numbers involved, an automated approach is the obvious alternative to arrive at the cell count. In this thesis, a software application is described that automatically segments, counts, and helps visualize the various cell bodies present in a sample mouse brain, by analyzing the images produced by the Knife-Edge Scanning Microscope (KESM) at the Brain Networks Laboratory. The process is described essentially in five stages: Image acquisition, Pre- Processing, Processing, Analysis and Refinement, and finally Visualization. Nissl staining is a staining mechanism that is used on the mouse brain sample to highlight the cell bodies of our interest present in the brain, namely neurons, granule cells and interneurons. This stained brain sample is embedded in solid plastic and imaged by the KESM, one section at a time. The volume that is digitized by this process is the data that is used for the purpose of segmentation. While most sections of the mouse brain tend to be comprised of sparsely populated neurons and red blood cells, certain sections near the cerebellum exhibit a very high density and population of smaller granule cells, which are hard to segment using simpler image segmentation techniques. The problem of the sparsely populated regions is tackled using a combination of connected component labeling and template matching, while the watershed algorithm is applied to the regions of very high density. Finally, the marching cubes algorithm is used to convert the volumetric data to a 3D polygonal representation. Barring a few initializations, the process goes ahead with minimal manual intervention. A graphical user interface is provided to the user to view the processed data in 2D or 3D. The interface offers the freedom of rotating and zooming in/out of the 3D model, as well as viewing only cells the user is interested in analyzing. The segmentation results achieved by our automated process are compared with those obtained by manual segmentation by an independent expert.

<p>A Positive Electron Tomography/Computed Tomography devise was installed in theX-ray section at US Linköping in May 2007. Positive Electron Tomography examinations with 18F-fluoro-deoxy-glucose are mainly used for tumor examinations. During 2007 occurred approximately 200 examinations and in 2008 600 are planned. Today there are two reconstruction methods commercially available, Filtered Back projection and Maximum Likelihood Expectation Maximiza tion, used in the faster version called Ordered Subsets Expectation Maximization. The image quality in Positive Electron Tomography depends on the choice of reconstruction method and the settings of its parameters. We have performed a physical phantom study with Positive Electron Tomography to determine optimal parameters for the iterative reconstruction algorithm Ordered Subsets Expectation Maximization. To find out whether or not the quality of the image can be improved, so that the patient received radiation dose and/or examination time can be lowered. The phantom used was a NEMA IEC Body PhantomTM, designed to mimic smallhot lesions typical in 18F, Fluorine-18 PET, and all calculations were done according to the NEMA NU2-2001 protocol.</p><p>The main conclusion from this project is that a higher level of contrast can be reached, compared to the one clinically obtained today. Using more iterations then recommended from the manufacturer.</p> / <p>I maj 2007 installerades en Positiv Elektron Tomografi /DatoriseradTomografi-kamera, PET/CT, i Röntgenavdelningen Linköping US. PET med 18F-fluoro-deoxy-glucose används huvudsakligen för tumörundersökningar.2007 genomfördes ca 200 undersökningar, och för 2008 är ytterligare 600 planerade. Idag finns två olika bildrekonstruktionsmetoder kliniskt tillgängliga; Filtered Back projection och Maximum Likelihood Expectation Maximization, där den  vidareutvecklade versionen kallad Ordered Subsets Expectation Maximizationanvänds. Bildkvalitén från en Positive Electron Tomographykamera påverkas av valet av rekonstruktionsmetod och dess ingående parametrar.</p><p>I detta projekt har en fantomstudie genomförts med syfte att bestämma de optimala parametrarna för den iterativa metoden Ordered Subsets Expectation Maximization. För att utreda huruvida stråldosen och/eller undersöknings tiden kan minskas. Det testfantom som användes var en NEMA IEC Body PhantomTM. Projektet följde metoden angiven i NEMA NU2-2001 protokollet. Det resultaten visar är att de rekommenderade inställningarna från tillverkaren inte är de optimala.</p>

<p>A Positive Electron Tomography/Computed Tomography devise was installed in the X-ray section at US Linköping in May 2007. Positive Electron Tomography examinations with 18F-fluoro-deoxyglucose are mainly used for tumor examinations. During 2007 occurred approximately 200 examinations and in 2008 600 are planned.Today there are two reconstruction methods commercially available, Filtered Back projection and Maximum Likelihood Expectation Maximiza tion, used in the faster version called Ordered Subsets Expectation Maximization. The image quality in Positive Electron Tomography depends on the choice of reconstruction method and the settings of its parameters. We have performed a physical phantom study with Positive Electron Tomography to determine optimal parameters for the iterativereconstruction algorithm Ordered Subsets Expectation Maximization. To find out whether or not the quality of the image can be improved, so that the patient received radiation dose and/or examination time can be lowered. The phantom used was a NEMA IEC Body PhantomTM, designed to mimic small hot lesions typicalin 18F, Fluorine-18 PET, and all calculations were done according to the NEMA NU2-2001 protocol.</p><p>The main conclusion from this project is that a higher level of contrastcan be reached, compared to the one clinically obtained today. Using more iterations then recommended from the manufacturer.</p>

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: digital x-ray imaging; pixel size; scintillator. Includes bibliographical references (p. 57-59).

Cancer is the second leading cause of death in the United States, and its early diagnosis is critical to improving treatment options and patient outcomes. In autofluorescence (AF) imaging, light of controlled wavelengths is projected onto tissue, absorbed by specific molecules, and re-emitted at longer wavelengths. Images of re-emitted light are used together with spectral information to infer tissue functional information and diagnosis. This dissertation describes AF imaging studies of three different organs using data collected from fresh human surgical specimens. In the ovary study, illumination was at 365 nm, and images were captured at 8 emission wavelengths. Measurements from a multispectral imaging system and fiber optic probe were used to map tissue diagnosis at every image pixel. For the colon and pancreas studies, instrumentation was developed extending AF imaging capability to sub-300 nm excitation. Images excited in the deep UV revealed tryptophan and protein content which are believed to change with disease state. Several excitation wavelength bands from 280 nm to 440 nm were investigated. Microscopic AF images collected in the pancreas study included both cultured and primary cells. Several findings are reported. A method of transforming fiber optic probe spectra for direct comparison with imager spectra was devised. Normalization of AF data by green reflectance data was found useful in correcting hemoglobin absorption. Ratio images, both AF and reflectance, were formulated to highlight growths in the colon. Novel tryptophan AF images were found less useful for colon diagnostics than the new ratio techniques. Microscopic tryptophan AF images produce useful visualization of cellular protein content, but their diagnostic value requires further study.