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We propose an algorithm for iterative, motion-compensated reconstruction of cardiac-gated SPECT. Dose limitations in SPECT lead to high level of noise in the projection data and further in the reconstructed images. Several reconstruction techniques have been reported to mitigate for the noise effects but they process each time frame individually and do not account for data temporal correlation. Advanced...
In this paper we aim to develop a computationally-efficient image-segmentation procedure for detection and quantification of soft plaques in coronary arteries from multidetector CT images. The proposed method consists of three steps: extraction of the arterial lumen centerline, segmentation of the lumen and arterial wall based on a locally-adaptive mixture-model using the expectation- maximization...
In this paper we present new detectors for additive watermarks when the power of the watermark is unknown. These detectors are based on modeling the image using student-t statistics. As a result, due to the generative properties of the student-t density function, such models are spatially adaptive and the Expectation-Maximization algorithm can be used to obtain maximum likelihood estimates of their...
In this paper we propose a unified image reconstruction procedure for dynamic images from traditional gated SPECT acquisition. We divide the cardiac cycle into a number of gate intervals as in gated SPECT, but treat the tracer distribution for each gate as a time-varying signal. By using dynamic expectation maximization and motion-compensated temporal regularization, our reconstruction procedure can...
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