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This thesis presents a part of the research work at Virginia Tech on developing a prototype automatic luggage scanner for explosive detection, and it deals with the automatic detection of elongated objects (detonators) in x-ray images using matched filtering, the Hough transform, and information fusion techniques. A sophisticated algorithm has been developed for detonator detection in x-ray images, and computer software utilizing this algorithm was programmed to implement the detection on both UNIX and PC platforms. A variety of template matching techniques were evaluated, and the filtering parameters (template size, template model, thresholding value, etc.) were optimized. A variation of matched filtering was found to be reasonably effective, while a Gabor-filtering method was found not to be suitable for this problem. The developed software for both single orientations and multiple orientations was tested on x-ray images generated on AS&E and Fiscan inspection systems, and was found to work well for a variety of images. The effects of object overlapping, luggage position on the conveyor, and detonator orientation variation were also investigated using the single-orientation algorithm. It was found that the effectiveness of the software depended on the extent of overlapping as well as on the objects the detonator overlapped. The software was found to work well regardless of the position of the luggage bag on the conveyor, and it was able to tolerate a moderate amount of orientation change. / Master of Science

<p>To properly display digital X-ray images for visual diagnosis, a proper display range needs to be identified. This can be difficult when the image contains collimators or large background areas which can dominate the histograms. Also, when there are both underexposed and overexposed areas in the image it is difficult to display these properly at the same time. The purpose of this thesis is to find a way to solve these problems. A few different approaches are evaluated to find their strengths and weaknesses. Based on Local Histogram Equalization, a new method is developed to put various constraints on the mapping. These include alternative ways to perform the histogram calculations and how to define the local histograms. The new method also includes collimator detection and background suppression to keep irrelevant parts of the image out of the calculations. Results show that the new method enables proper display of both underexposed and overexposed areas in the image simultaneously while maintaining the natural look of the image. More testing is required to find appropriate parameters for various image types.</p>

To properly display digital X-ray images for visual diagnosis, a proper display range needs to be identified. This can be difficult when the image contains collimators or large background areas which can dominate the histograms. Also, when there are both underexposed and overexposed areas in the image it is difficult to display these properly at the same time. The purpose of this thesis is to find a way to solve these problems. A few different approaches are evaluated to find their strengths and weaknesses. Based on Local Histogram Equalization, a new method is developed to put various constraints on the mapping. These include alternative ways to perform the histogram calculations and how to define the local histograms. The new method also includes collimator detection and background suppression to keep irrelevant parts of the image out of the calculations. Results show that the new method enables proper display of both underexposed and overexposed areas in the image simultaneously while maintaining the natural look of the image. More testing is required to find appropriate parameters for various image types.

Les séquences fluoroscopiques, acquises à de faibles doses de rayons X, sont utilisées au cours de certaines opérations médicales pour guider le personnel médical dans ces actes. Cependant, la qualité des images obtenues est inversement proportionnelle à cette dose. Nous proposons dans ces travaux un algorithme de réduction de bruit permettant de compenser les effets d'une réduction de la dose d'acquisition et donc garantissant une meilleure protection pour le patient et le personnel médical. Le filtrage développé est un filtre spatio-temporel s'appuyant sur les représentations multi-échelles 2D des images de la séquence pour de meilleures performances. Le filtre temporel récursif d'ordre 1 et compensé en mouvement permet une forte réduction de bruit. Il utilise une détection et un suivi des objets de la séquence. Ces deux étapes déterminent le filtrage spatio-temporel de chaque coefficient multi-échelles. Le filtrage spatial est un seuillage contextuel utilisant le voisinage multi-échelles des coefficients pour éviter l'apparition d'artefacts de forme dans les images reconstruites. La méthode proposée est testée dans deux espaces multi-échelles différents, les curvelets et les ondelettes complexes suivant l'arbre dual. Elle offre des performances supérieures à celles des meilleures méthodes de l'état de l'art. / Acquired with low doses of X-rays, fluoroscopic sequences are used to guide the medical staff during some medical procedures. However, image quality is inversely proportional to acquisition doses. We present here a noise reduction algorithm compensating for the effects of an acquisition at a reduced dose. Such a reduction enables better health protection for the patient as well as for the medical staff. The proposed method is based on a spatio-temporal filter applied on the 2D multi-scales representations of the sequence images to allow for a greater noise reduction. The motion-compensated, recursive filter acccounts for most of the noise reduction. It is composed of a detection and pairing step, which output determines how a coefficient is filtered. Spatial filtering is based on a contextual thresholding to avoid introducing shape-like artifacts. We compare this filtering both in the curvelet and dual-tree complex wavelet domains and show it offers better results than state-of-the-art methods.

<p>Direct conversion flat panel x-ray image sensors based on using a photoconductor with an active matrix array provide excellent images. These image sensors are suitable for replacing the present day x-ray film/screen cassette to capture an x-ray image electronically, and hence enable a clinical transition to digital radiography. The performance of these sensors depends critically on the selection and design of the photoconductor. This work quantitatively studies the combined effects of the detector geometry (pixel size and detector thickness), operating conditions (x-ray energy and applied electric field) and charge transport properties (e.g., carrier trapping and recombination) of the photoconductor on the detector performance by developing appropriate detector models. In this thesis, the models for calculating the x-ray sensitivity, resolution in terms of the modulation transfer function (MTF), detective quantum efficiency (DQE), and ghosting of x-ray image detectors have been developed. The modeling works are based on the physics of the individual phenomena and the systematic solution of the fundamental physical equations in the photoconductor layer: (1) semiconductor continuity equation (2) Poissons equation (3) trapping rate equations. The general approach of this work is to develop models in normalized coordinates to describe the results of different photoconductive x-ray image detectors. These models are applied to a-Se, polycrystalline HgI_2 and polycrystalline CdZnTe photoconductive detectors for diagnostic medical x-ray imaging applications (e,g., mammography, chest radiography and fluoroscopy). The models show a very good agreement with the experimental results.</p><p>The research presented in this thesis shows that the imaging performances (e.g., sensitivity, MTF, DQE and ghosting) can be improved by insuring that the carrier with higher mobility-lifetime product is drifted towards the pixel electrodes. The carrier schubwegs have to be several times greater, and the absorption depth has to be at least two times smaller than the photoconductor thickness for achieving sufficient sensitivity. Having smaller pixels is advantageous in terms of higher sensitivity by ensuring that the carrier with the higher mobility-lifetime product is drifted towards the pixel electrodes. </p><p>A model for calculating zero spatial frequency detective quantum efficiency, DQE (0), has been developed by including incomplete charge collection and x-ray interaction depth dependent conversion gain. The DQE(0) analyses of a-Se detectors for fluoroscopic applications show that there is an optimum photoconductor thickness, which maximizes the DQE(0) under a constant voltage operation. The application of DQE(0) model to different potential photoconductive detectors for fluoroscopic applications show that, in addition to high quantum efficiency, both high conversion gain and high charge collection efficiency are required to improve the DQE performance of an x-ray image detector.</p><p>An analytical expression of MTF due to distributed carrier trapping in the bulk of the photoconductor has been derived using the trapped charge distribution across the photoconductor. Trapping of the carriers that move towards the pixel electrodes degrades the MTF performance, whereas trapping of the other type of carriers improves the sharpness of the x-ray image.</p><p>The large signal model calculations in this thesis show an upper limit of small signal models of x-ray image detectors. The bimolecular recombination between drifting carriers plays practically no role on charge collection in a-Se detectors up to the total carrier generation rate q0 of 10^18 EHPs/m^2-s. The bimolecular recombination has practically no effect on charge collection in a-Se detectors for diagnostic medical x-ray imaging applications. </p><p>A model for examining the sensitivity fluctuation mechanisms in a-Se detectors has been developed. The comparison of the model with the experimental data reveals that the recombination between trapped and the oppositely charged drifting carriers, electric field dependent charge carrier generation and x-ray induced new deep trap centers are mainly responsible for the sensitivity fluctuation in biased a-Se x-ray detectors. </p><p>The modeling works in this thesis identify the important factors that limit the detector performance, which can ultimately lead to the reduction of patient exposure/dose consistent with better diagnosis for different diagnostic medical x-ray imaging modalities. The quantitative analyses presented in this thesis show that the detector structure is just as important to the overall performance of the detector as the material properties of the photoconductor itself.</p>

<p>Direct conversion flat panel x-ray image sensors based on using a photoconductor with an active matrix array provide excellent images. These image sensors are suitable for replacing the present day x-ray film/screen cassette to capture an x-ray image electronically, and hence enable a clinical transition to digital radiography. The performance of these sensors depends critically on the selection and design of the photoconductor. This work quantitatively studies the combined effects of the detector geometry (pixel size and detector thickness), operating conditions (x-ray energy and applied electric field) and charge transport properties (e.g., carrier trapping and recombination) of the photoconductor on the detector performance by developing appropriate detector models. In this thesis, the models for calculating the x-ray sensitivity, resolution in terms of the modulation transfer function (MTF), detective quantum efficiency (DQE), and ghosting of x-ray image detectors have been developed. The modeling works are based on the physics of the individual phenomena and the systematic solution of the fundamental physical equations in the photoconductor layer: (1) semiconductor continuity equation (2) Poissons equation (3) trapping rate equations. The general approach of this work is to develop models in normalized coordinates to describe the results of different photoconductive x-ray image detectors. These models are applied to a-Se, polycrystalline HgI_2 and polycrystalline CdZnTe photoconductive detectors for diagnostic medical x-ray imaging applications (e,g., mammography, chest radiography and fluoroscopy). The models show a very good agreement with the experimental results.</p><p>The research presented in this thesis shows that the imaging performances (e.g., sensitivity, MTF, DQE and ghosting) can be improved by insuring that the carrier with higher mobility-lifetime product is drifted towards the pixel electrodes. The carrier schubwegs have to be several times greater, and the absorption depth has to be at least two times smaller than the photoconductor thickness for achieving sufficient sensitivity. Having smaller pixels is advantageous in terms of higher sensitivity by ensuring that the carrier with the higher mobility-lifetime product is drifted towards the pixel electrodes. </p><p>A model for calculating zero spatial frequency detective quantum efficiency, DQE (0), has been developed by including incomplete charge collection and x-ray interaction depth dependent conversion gain. The DQE(0) analyses of a-Se detectors for fluoroscopic applications show that there is an optimum photoconductor thickness, which maximizes the DQE(0) under a constant voltage operation. The application of DQE(0) model to different potential photoconductive detectors for fluoroscopic applications show that, in addition to high quantum efficiency, both high conversion gain and high charge collection efficiency are required to improve the DQE performance of an x-ray image detector.</p><p>An analytical expression of MTF due to distributed carrier trapping in the bulk of the photoconductor has been derived using the trapped charge distribution across the photoconductor. Trapping of the carriers that move towards the pixel electrodes degrades the MTF performance, whereas trapping of the other type of carriers improves the sharpness of the x-ray image.</p><p>The large signal model calculations in this thesis show an upper limit of small signal models of x-ray image detectors. The bimolecular recombination between drifting carriers plays practically no role on charge collection in a-Se detectors up to the total carrier generation rate q0 of 10^18 EHPs/m^2-s. The bimolecular recombination has practically no effect on charge collection in a-Se detectors for diagnostic medical x-ray imaging applications. </p><p>A model for examining the sensitivity fluctuation mechanisms in a-Se detectors has been developed. The comparison of the model with the experimental data reveals that the recombination between trapped and the oppositely charged drifting carriers, electric field dependent charge carrier generation and x-ray induced new deep trap centers are mainly responsible for the sensitivity fluctuation in biased a-Se x-ray detectors. </p><p>The modeling works in this thesis identify the important factors that limit the detector performance, which can ultimately lead to the reduction of patient exposure/dose consistent with better diagnosis for different diagnostic medical x-ray imaging modalities. The quantitative analyses presented in this thesis show that the detector structure is just as important to the overall performance of the detector as the material properties of the photoconductor itself.</p>

The subject of this thesis is a method proposed for automated evaluation of the parameters of X-ray of cystic disorders in human jawbones. The main problem in medical diagnostic is the low repeatability due to the subjective evaluation of images without using a tool for image processing. In this thesis are described the basic steps of image processing, various methods of image segmentation and chosen segmentation method live-wire. Selected segments were processed in the ImageJ Java environment. In the cystic regions their basic statistical and shape properties were evaluated. The obtained values were used for learning the classification model (decision tree) in the environment RapidMiner. This model was used to create a plug-in for automatic classification of the type of cysts in the program ImageJ.

This thesis deals with design and realization of methods of preprocessing of X-ray images and its storage. In the first part of this thesis, there were designed and implemented methods for preprocessing of series of X-ray images such as averaging after image registration or merging of images to a HDR image using Debevec method. In the following part of the thesis, there was done a literary research of data formats based on which was implemented a library for x-ray images storage. Both implemented methods allow to reduce a random noise by merging a series of images. Application of the Debevec method also allow to increase a dynamic range of image.

In this dissertation, the accuracy and reliability of non-linear finite element computations in application to surgical simulation is evaluated. The evaluation is performed through comparison between the experiment and finite element analysis of indentation of soft tissue phantom and human brain phantom. The evaluation is done in terms of the forces acting on the cylindrical Aluminium indenter and deformation of the phantoms due to these forces. The deformation of the phantoms is measured by tracking 3D motions of X-ray opaque markers implanted in the direct neighbourhood under the indenter using a custom-made biplane X-ray image intensifiers (XRII) system. The phantoms are made of Sylgard® 527 gel to simulate the hyperelastic constitutive behaviour of the brain tissue. The phantoms are prepared layer by layer to facilitate the implantation of the X-ray opaque markers. The modelling of soft tissue phantom indentation and human brain phantom indentation is performed using the ABAQUSTM/Standard finite element solver. Realistic geometry model of the human brain phantom obtained from Magnetic Resonance images is used. Specific constitutive properties of the phantom layers determined through uniaxial compression tests are used in the model. The models accurately predict the indentation force-displacement relations and marker displacements in both soft tissue phantom indentation and human brain phantom indentation. Good agreement between the experimental and modelling results verifies the reliability and accuracy of the finite element analysis techniques used in this study and confirms the predictive power of these techniques in application to surgical simulation.