Showing papers by "Charles R. Dyer published in 2006"

Segmentation of elastographic images using a coarse-to-fine active contour model

Abstract: Delineation of radiofrequency-ablation-induced coagulation (thermal lesion) boundaries is an important clinical problem that is not well addressed by conventional imaging modalities. Elastography, which produces images of the local strain after small, externally applied compressions, can be used for visualization of thermal coagulations. This paper presents an automated segmentation approach for thermal coagulations on 3-D elastographic data to obtain both area and volume information rapidly. The approach consists of a coarse-to-fine method for active contour initialization and a gradient vector flow, active contour model for deformable contour optimization with the help of prior knowledge of the geometry of general thermal coagulations. The performance of the algorithm has been shown to be comparable to manual delineation of coagulations on elastograms by medical physicists (r = 0.99 for volumes of 36 radiofrequency-induced coagulations). Furthermore, the automatic algorithm applied to elastograms yielded results that agreed with manual delineation of coagulations on pathology images (r = 0.96 for the same 36 lesions). This algorithm has also been successfully applied on in vivo elastograms.

Sequential monte carlo methods for physically based rendering

Abstract: The goal of global illumination is to generate photo-realistic images by taking into account all the light interactions in the scene. It does so by simulating light transport behaviors based on physical principles. The main challenge of global illumination is that simulating the complex light interreflections is very expensive. In this dissertation, a novel statistical framework for physically based rendering in computer graphics is presented based on sequential Monte Carlo (SMC) methods. This framework can substantially improve the efficiency of physically based rendering by adapting and reusing the light path samples without introducing bias. Applications of the framework to a variety of problems in global illumination are demonstrated. For the task of photo-realistic rendering, only light paths that reach the image plane are important because only those paths contribute to the final image. A visual importance-driven algorithm is proposed to generate visually important paths. The photons along those paths are also cached in photon maps for further reuse. To handle difficult paths in the path space, a technique is presented for including user-selected paths in the sampling process. Then, a more general statistical method for light path sample adaptation and reuse is studied in the context of sequential Monte Carlo. Based on the population Monte Carlo method, an unbiased adaptive sampling method is presented that works on a population of samples. The samples are sampled and resampled through distributions that are modified over time. Information found at one iteration can be used to guide subsequent iterations without introducing bias in the final result. After obtaining samples from multiple distributions, an optimal control variate algorithm is developed that allows samples from multiple distribution functions to be combined optimally.

Face Cyclographs for Recognition

Abstract: A new representation of faces, called face cyclographs, is introduced for face recognition that incorporates all views of a rotating face into a single image. The main motivation for this representation comes from recent psychophysical studies that show that humans use continuous image sequences in object recognition. Face cyclographs are created by slicing spatiotemporal face volumes that are constructed automatically based on real-time face detection. This representation is a compact, multiperspective, spatiotemporal description. To use face cyclographs for recognition, a dynamic programming based algorithm is developed. The motion trajectory image of the eye slice is used to analyze the approximate single-axis motion and normalize the face cyclographs. Using normalized face cyclographs can speed up the matching process. Experimental results on more than 100 face videos show that this representation efficiently encodes the continuous views of faces.