Homotopic non-local regularized reconstruction from sparse positron emission tomography measurements

Homotopic non-local regularized reconstruction from sparse positron emission tomography measurements

BACKGROUND Positron emission tomography scanners collect measurements of a patient's in vivo radiotracer distribution. The system detects pairs of gamma rays emitted indirectly by a positron-emitting radionuclide (tracer), which is introduced into the body on a biologically active molecule, and the tomograms must be reconstructed from projections. The reconstruction of tomograms from the acquir...

Noise-compensated homotopic non-local regularized reconstruction for rapid retinal optical coherence tomography image acquisitions

BACKGROUND Optical coherence tomography (OCT) is a minimally invasive imaging technique, which utilizes the spatial and temporal coherence properties of optical waves backscattered from biological material. Recent advances in tunable lasers and infrared camera technologies have enabled an increase in the OCT imaging speed by a factor of more than 100, which is important for retinal imaging wher...

Author's response to reviews Title:Noise-compensated Homotopic Non-local Regularized Reconstruction for Rapid Retinal Optical Coherence Tomography Image Acquisitions Authors:

Simultaneous Reconstruction in Dynamic Positron Emission Tomography

In this paper we study the problem of reconstructing simultaneously a sequence of images in a dynamic PET study. In our algorithm we will make use of the fact that the morphology does not change by much between adjacent frames. Together with a total variation prior this will be shown to reduce the noise level considerably, without corrupting the individuality of the frames. Simulation results a...

A Computational Framework for Total Variation-Regularized Positron Emission Tomography

In positron emission tomography, image data corresponds to measurements of emitted photons from a radioactive tracer in the subject. Such count data is typically modeled using a Poisson random variable, leading to the use of the negative-log Poisson likelihood fit-to-data function. Regularization is needed, however, in order to guarantee reconstructions with minimal artifacts. Given that tracer...