The percutaneous revascularization of chronic total occlusions represents a major challenge to interventional cardiologists. Procedural success is currently limited by the inadequate soft-tissue contrast of x-ray fluoroscopy and the inability to visualize the position and orientation of a revascularization device with respect to the lesion and the vessel wall. In this thesis methods are developed that enable the percutaneous revascularization of occlusive lesions to be guided using magnetic resonance (MR) imaging. Unlike x-rays, MR has excellent soft-tissue contrast and this can be exploited to provide valuable information regarding the composition and geometry of the lesion. The first method is a robust and redundant technique for determining the position and orientation of a catheter inside an MR scanner. The technique uses phase information introduced into the MR signal by a small receive coil located at the distal tip of the catheter. The technique is developed theoretically and is demonstrated with a feasibility experiment. A forward-looking intravascular imaging catheter is then presented that is capable of acquiring of high-resolution MR images of occlusive lesions and the vessel wall in front of the catheter. The imaging catheter consists of two orthogonal receive coils located at the distal tip of the catheter. The use of the imaging catheter is demonstrated in phantoms and in vivo. A third method enables active visualization of MR compatible guidewires. The method utilizes a catheter-based pick-up coil that is magnetically coupled to the guidewire. The proposed technique enables one to concentrate all active components on a catheter thereby facilitating the use of safety features. Complete characterization is presented theoretically and validated experimentally. In addition, the use of a practical catheter device is demonstrated in an in situ environment. Finally, future work required for the development of an integrated catheter-based device for the MR-guided revascularization of chronic total occlusions is discussed.

Per al càlcul de la il·luminació global per a la síntesi d'imatges d'escenaris virtuals s'usen mètodes físicament acurats com a radiositat o el ray-tracing. Aquests mètodes són molt potents i capaços de generar imatges de gran realisme, però són molt costosos. A aquesta tesi presenta algunes tècniques per simular i/o accelerar el càlcul de la il·luminació global. La tècnica de les obscurances es basa en la suposició que com més amagat és un punt a l'escena, més fosc s'ha de veure. Es calcula analitzant l'entorn geomètric del punt i ens dóna un valor per a la seva il·luminació indirecta, que no és físicament acurat, però sí aparentment realista.Aquesta tècnica es millora per a entorns en temps real com els videojocs. S'aplica també a entorns de ray-tracing per a la generació d'imatges realistes. En aquest context, el càlcul de seqüències de frames per a l'animació de llums i càmeres s'accelera enormement reusant informació entre frames.Les obscurances serveixen per a simular la il·luminació indirecta d'una escena. La llum directa es calcula apart i de manera independent. El desacoblament de la llum directa i la indirecta és una gran avantatge, i en treurem profit. Podem afegir fàcilment l'efecte de coloració entre objectes sense afegir temps de càlcul. Una altra avantatge és que per calcular les obscurances només hem d'analitzar un entorn limitat al voltant del punt.Per escenes virtuals difuses, la radiositat es pot precalcular i l'escena es pot navegar amb apariència realista, però si un objecte de l'escena es mou en un entorn dinàmic en temps real, com un videojoc, el recàlcul de la il·luminació global de l'escena és prohibitiu. Com les obscurances es calculen en un entorn limitat, es poden recalcular en temps real per a l'entorn de l'objecte que es mou a cada frame i encara aconseguir temps real.A més, podem fer servir les obscurances per a calcular imatges de gran qualitat, o per seqüències d'imatges per una animació, com en el ray-tracing. Això ens permet tractar materials no difusos i investigar l'ús de tècniques normalment difuses com les obscurances en entorns generals. Quan la càmera està estàtica, l'ús d'animació de llum només afecta la il·luminació directa, i si usem obscurances per a la llum indirecta, gràcies al seu desacoblament, el càlcul de sèries de frames per a una animació és molt ràpid. El següent pas és afegir animació de càmera, reusant els valors de les obscurances entre frames. Aquesta última tècnica de reús d'informació de la il·luminació del punt d'impacte entre frames la podem usar per a tècniques acurades d'il·luminació global com el path-tracing, i nosaltres estudiem com reusar aquesta informació de manera no esbiaixada. A més, estudiem diferents tècniques de mostreig per a la semi-esfera, i les obscurances es calculen amb una nova tècnica, aplicant depth peeling amb GPU. / To compute global illumination solutions for rendering virtual scenes, physically accurate methods based on radiosity or ray-tracing are usually employed. These methods, though powerful and capable of generating images with high realism, are very costly. In this thesis, some techniques to simulate and/or accelerate the computation of global illumination are studied. The obscurances technique is based on the supposition that the more occluded is a point in the scene, the darker it will appear. It is computed by analyzing the geometric environment of the point and gives a value for the indirect illumination for the point that is, though not physically accurate, visually realistic. This technique is enhanced and improved in real-time environments as videogames. It is also applied to ray-tracing frameworks to generate realistic images. In this last context, sequences of frames for animation of lights and cameras are dramatically accelerated by reusing information between frames.The obscurances are computed to simulate the indirect illumination of a scene. The direct lighting is computed apart and in an independent way. The decoupling of direct and indirect lighting is a big advantage, and we will take profit from this. We can easily add color bleeding effects without adding computation time. Another advantage is that to compute the obscurances we only need to analyze a limited environment around the point. For diffuse virtual scenes, the radiosity can be precomputed and we can navigate the scene with a realistic appearance. But when a small object moves in a dynamic real-time virtual environment, as a videogame, the recomputation of the global illumination of the scene is prohibitive. Thanks to the limited reach of the obscurance computation, we can recompute the obscurances only for the limited environment of the moving object for every frame and still have real-time frame rates. Obscurances can also be used to compute high quality images, or sequences of images for an animation, in a ray-tracing-like. This allows us to deal with non-diffuse materials and to research the use of a commonly diffuse technique as obscurances in general environments. For static cameras, using light animation only affects to direct lighting, and if we use obscurances for the indirect lighting, thanks to the decoupling of direct and indirect illumination, the computation of a series of frames for the animation is very fast. The next step is to add camera animation, reusing the obscurances results between frames. Using this last technique of reusing the illumination of the hit points between frames for a true global illumination technique as path tracing, we study how we can reuse this information in an unbiased way. Besides, a study of different sampling techniques for the hemisphere is made, obscurances are computed with the depth-peeling technique and using GPU.

Object tracking is an important problem with wide ranging applications. The purpose is to detect object contours and track their motion in a video. Issues of concern are to be able to map objects correctly between two frames, and to be able to track through occlusion. This thesis discusses a novel framework for the purpose of object tracking which is inspired from image registration and segmentation models. Occlusion of objects is also detected and handled in this framework in an appropriate manner. The main idea of our tracking framework is to reconstruct the sequence of images in the video. The process involves deforming all the objects in a given image frame, called the initial frame. Regularization terms are used to govern the deformation of the shape of the objects. We use elastic and viscous fluid model as the regularizer. The reconstructed frame is formed by combining the deformed objects with respect to the depth ordering. The correct reconstruction is selected by parameters that minimize the difference between the reconstruction and the consecutive frame, called the target frame. These parameters provide the required tracking information, such as the contour of the objects in the target frame including the occluded regions. The regularization term restricts the deformation of the object shape in the occluded region and thus gives an estimate of the object shape in this region. The other idea is to use a segmentation model as a measure in place of the frame difference measure. This is separate from image segmentation procedure, since we use the segmentation model in a tracking framework to capture object deformation. Numerical examples are presented to demonstrate tracking in simple and complex scenes, alongwith occlusion handling capability of our model. Segmentation measure is shown to be more robust with regard to accumulation of tracking error.

Ultrasound (US) volume data is noisy, so traditional methods for direct volume rendering (DVR) are less appropriate. Improved methods or new techniques are required. There are furthermore a high performance requirement and limited pre-processing to be considered in order for it to be used interactively, since the volume data might be time-varying. There exist numerous techniques for improving visual perception of volume rendering, and while some perform well and produce a visually enhanced result, many are designed and compared for use with medical data that has a high signal-to-noise ratio. This master thesis describe and compare recent methods for DVR illumination, in the form of ambient occlusion or direct/indirect lighting from an external light source. New designs and modifications are introduced for efficiently and effectively enhancing the visual quality of DVR with US data. Furthermore, this thesis addresses the issue of how clipping is performed during rendering and for the different illumination techniques, which is commonly used in ultrasound visualization. This diploma work was conducted at Siemens Corporate Research in Princeton, NJ where the partially open source framework XIP is developed. The framework was extended further to include modern methods for DVR illumination that are described in detail within this thesis. Finally, presented results show that several methods can be used to visually enhance the visualization within highly interactive frame-rates.

Object tracking is an important problem with wide ranging applications. The purpose is to detect object contours and track their motion in a video. Issues of concern are to be able to map objects correctly between two frames, and to be able to track through occlusion. This thesis discusses a novel framework for the purpose of object tracking which is inspired from image registration and segmentation models. Occlusion of objects is also detected and handled in this framework in an appropriate manner. The main idea of our tracking framework is to reconstruct the sequence of images in the video. The process involves deforming all the objects in a given image frame, called the initial frame. Regularization terms are used to govern the deformation of the shape of the objects. We use elastic and viscous fluid model as the regularizer. The reconstructed frame is formed by combining the deformed objects with respect to the depth ordering. The correct reconstruction is selected by parameters that minimize the difference between the reconstruction and the consecutive frame, called the target frame. These parameters provide the required tracking information, such as the contour of the objects in the target frame including the occluded regions. The regularization term restricts the deformation of the object shape in the occluded region and thus gives an estimate of the object shape in this region. The other idea is to use a segmentation model as a measure in place of the frame difference measure. This is separate from image segmentation procedure, since we use the segmentation model in a tracking framework to capture object deformation. Numerical examples are presented to demonstrate tracking in simple and complex scenes, alongwith occlusion handling capability of our model. Segmentation measure is shown to be more robust with regard to accumulation of tracking error.

This thesis looks at how the GPU¡¦s processing of objects can be simplified (from the programmer¡¦s point of view) and improved (from the run-time point of view). We propose both software and hardware modifications for automatic occlusion detection to avoid rendering occluded objects. We also consider subobjects. The method takes advantage of partial occlusion opportunities and also allow for parts of an object to self-occlude other parts of the same object. Their rendering sequence can be dynamically reordered at minimal cost, thereby increasing the self-occlusion opportunities within the object. In addition, this thesis investigates methods of automatic hull creation and subobject creation.

Thesis (M.S.)--West Virginia University, 2004. / Title from document title page. Document formatted into pages; contains vii, 56 p. : ill. (some col.). Vita. Includes abstract. Includes bibliographical references (p. 36-39).

Thesis (M.S.)--University of Michigan, 1999. / Includes bibliographical references.

The objective of this Thesis research is to develop algorithms for temporally consistent semantic segmentation in videos. Though many different forms of semantic segmentations exist, this research is focused on the problem of temporally-consistent holistic scene understanding in outdoor videos. Holistic scene understanding requires an understanding of many individual aspects of the scene including 3D layout, objects present, occlusion boundaries, and depth. Such a description of a dynamic scene would be useful for many robotic applications including object reasoning, 3D perception, video analysis, video coding, segmentation, navigation and activity recognition. Scene understanding has been studied with great success for still images. However, scene understanding in videos requires additional approaches to account for the temporal variation, dynamic information, and exploiting causality. As a first step, image-based scene understanding methods can be directly applied to individual video frames to generate a description of the scene. However, these methods do not exploit temporal information across neighboring frames. Further, lacking temporal consistency, image-based methods can result in temporally-inconsistent labels across frames. This inconsistency can impact performance, as scene labels suddenly change between frames. The objective of our this study is to develop temporally consistent scene descriptive algorithms by processing videos efficiently, exploiting causality and data-redundancy, and cater for scene dynamics. Specifically, we achieve our research objectives by (1) extracting geometric context from videos to give broad 3D structure of the scene with all objects present, (2) Detecting occlusion boundaries in videos due to depth discontinuity, (3) Estimating depth in videos by combining monocular and motion features with semantic features and occlusion boundaries.

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