We discuss the inverse problem associated with the propagation of the field autocorrelation of light through a highly scattering object like tissue. In the first part of the work, we reconstruct the optical absorption coefficient mu(a) and particle diffusion coefficient D(B) from simulated measurements which are integrals of a quantity computed from the measured intensity and intensity autocorr...

| In previous work we developed a list-mode iterative reconstruction algorithm (LMIRA) for SPECT applied to two dimensional image reconstruction. In the 2D case we calculated the emission radiance distribution on the circular enclosure of the object. This part is the forward projection. In the backprojection we sampled the radiance on the intermediate layer using the geometric properties of the...

We propose and study a block-iterative projections method for solving linear equations and/or inequalities. The method allows diagonal component-wise relaxation in conjunction with orthogonal projections onto the individual hyperplanes of the system, and is thus called diagonally-relaxed orthogonal projections (DROP). Diagonal relaxation has proven useful in accelerating the initial convergence...

OBJECTIVES The objective of this study was to compare the image quality and radiation dose of chest CT images reconstructed with a blend of adaptive statistical iterative reconstruction (ASIR) and filtered back-projection (FBP) with images generated using conventional FBP. METHODS Patients with chest CT re-examinations were alternately assigned to two scanners with different reconstruction te...

A novel technique for imaging spectroscopy is introduced. The technique makes use of an optical imaging system with a segmented aperture and intensity detector array on the imaging plane. The point spread function (PSF) of such a system can be adjusted by modifying the path lengths from the subapertures to the image plane, and the shape of the resulting point spread function will vary as a func...

METHOD FOR SOLVING LEAST-SQUARES PROBLEMS IN IMAGE RECONSTRUCTION H. D. Scolnik1 N. Echebest2 M.T. Guardarucci2 1 Departamento de Computación, Fac. de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina( [email protected]) 2 Departamento de Matemática, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Argentina ([email protected])

Future extreme adaptive optics (ExAO) systems have been suggested with up to 10(5) sensors and actuators. We analyze the computational speed of iterative reconstruction algorithms for such large systems. We compare a total of 15 different scalable methods, including multigrid, preconditioned conjugate-gradient, and several new variants of these. Simulations on a 128x128 square sensor/actuator g...

This paper describes a statistical iterative reconstruction method for X-ray CT based on a physical model that accounts for the polyenergetic X-ray source spectrum and the measurement nonlinearities caused by energy-dependentattenuation. The algorithm accommodates mixtures of tissues with known mass attenuation coefficients but unknown densities. We formulate a penalized-likelihood approach for...

We show in this paper how it is possible to reconstruct an image, in a very parallel way. using an asynchronous cellular array, with real-time performance. After introducing the image reconstruction problem, we present the main reconstruction techniques and the sequential algorithms. Then, we explain the manner to process these algorithms on a network. We describe this new integrated parallel a...

The statistics of photon counting by systems affected by deadtime are potentially important for statistical image reconstruction methods. We present a new way of analyzing the moments of the counting process for a counter system affected by various models of deadtime related to PET and SPECT imaging. We derive simple and exact expressions for the first and second moments of the number of record...