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PI-Line Based Fan-Beam Lambda Imaging without Singularities

Since the ionizing radiation may induce cancers and genetic damages in the patient, it is highly desirable to minimize the X-ray dose during a CT scan. As one of the local imaging techniques, the Lambda imaging reduces the X-ray dose and imaging time. But the existence of the singular values results in the low quality of the image. The broad applications of the Pi-lines proof that it can deal with the truncated projections effectively. In this work, we propose a new exact Lambda imaging algorithm based on Wang G's local imaging method and Pi-lines segment to reconstruct an image with utilizing a Gaussian kernel function convoluting the projection data. We also analyze how to choose the parameters of the Gaussian kernel function. Numerical simulations support our new reconstruction algorithm with high quality reconstruction image.