Showing papers on "Parametric Image published in 2001"

Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement

Abstract: In many image restoration/resolution enhancement applications, the blurring process, i.e., point spread function (PSF) of the imaging system, is not known or is known only to within a set of parameters. We estimate these PSF parameters for this ill-posed class of inverse problem from raw data, along with the regularization parameters required to stabilize the solution, using the generalized cross-validation method (GCV). We propose efficient approximation techniques based on the Lanczos algorithm and Gauss quadrature theory, reducing the computational complexity of the GCV. Data-driven PSF and regularization parameter estimation experiments with synthetic and real image sequences are presented to demonstrate the effectiveness and robustness of our method.

A Fast Nonlinear Method for Parametric Imaging of Myocardial Perfusion by Dynamic 13N-Ammonia PET

Abstract: A parametric image of myocardial perfusion (mL/min/g) is a quantitative image generated by fitting a tracer kinetic model to dynamic 13N-ammonia PET data on a pixel-by-pixel basis. There are several methods for such parameter estimation problems, including weighted nonlinear regression (WNLR) and a fast linearizing method known as Patlak analysis. Previous work showed that sigmoidal networks can be used for parameter estimation of mono- and biexponential models. The method used in this study is a hybrid of WNLR and sigmoidal networks called nonlinear regression estimation (NRE). The purpose of the study is to compare NRE with WNLR and Patlak analysis for parametric imaging of perfusion in the canine heart by 13N-ammonia PET. Methods: A simulation study measured the statistical performance of NRE, WNLR, and Patlak analysis for a probabilistic model of time–activity curves. Four canine subjects were injected with 740 MBq 13N-ammonia and scanned dynamically. Images were reconstructed with filtered backprojection and resliced into short-axis cuts. Parametric images of a single midventricular plane per subject were generated by NRE, WNLR, and Patlak analysis. Small regions of interest (ROIs) were drawn on each parametric image (8 ROIs per subject for a total of 32). Results: For the simulation study, the median absolute value of the relative error for a perfusion value of 1.0 mL/min/g was 16.6% for NRE, 17.9% for WNLR, 19.5% for Patlak analysis, and 14.5% for an optimal WNLR method (computable by simulation only). All methods are unbiased conditioned on a wide range of perfusion values. For the canine studies, the least squares line fits comparing NRE (y) and Patlak analysis (z) with WNLR (x) for all 32 ROIs were y = 1.02x − 0.028 and z = 0.90x + 0.019, respectively. Both NRE and Patlak analysis generate 128 × 128 parametric images in seconds. Conclusion: The statistical performance of NRE is competitive with WNLR and superior to Patlak analysis for parametric imaging of myocardial perfusion. NRE is a fast nonlinear alternative to Patlak analysis and other fast linearizing methods for parametric imaging. NRE should be applicable to many other tracers and tracer kinetic models.

Numerical simulation of spatial fluctuations in parametric image amplification

Abstract: We study the properties of the spatial fluctuations in the far-field parametric fluorescence output of a type 1 degenerate traveling-wave parametric amplifier. Results of a semi-classical simulation are compared with experiments in a LBO crystal. This simulation is then used to predict amplified images of a continuous background, in a phase-sensitive as well as in a phase-insensitive configuration.

Comparison of parametric FBP and OS-EM reconstruction algorithm images for PET dynamic study.

Abstract: An ordered subsets expectation maximization (OS-EM) algorithm is used for image reconstruction to suppress image noise and to make non-negative value images. We have applied OS-EM to a digital brain phantom and to human brain 18F-FDG PET kinetic studies to generate parametric images. A 45 min dynamic scan was performed starting injection of FDG with a 2D PET scanner. The images were reconstructed with OS-EM (6 iterations, 16 subsets) and with filtered backprojection (FBP), and K1, k2 and k3 images were created by the Marquardt non-linear least squares method based on the 3-parameter kinetic model. Although the OS-EM activity images correlated fairly well with those obtained by FBP, the pixel correlations were poor for the k2 and k3 parametric images, but the plots were scattered along the line of identity and the mean values for K1, k2 and k3 obtained by OS-EM were almost equal to those by FBP. The kinetic fitting error for OS-EM was no smaller than that for FBP. The results suggest that OS-EM is not necessarily superior to FBP for creating parametric images.

Phase-sensitive parametric image amplification: application to noiseless image amplification

Abstract: We report semi-classical numeric simulations of the quantum spatial fluctuations in parametric amplification of images limited by the shot noise. Noiseless amplification of images is demonstrated by the use of a degenerate type 2 phase sensitive amplifier.

Estimation of coronary blood flow by contrast propagation using X-ray cineangiographic images

Abstract: The estimation of coronary blood flow by computational techniques from X-ray angiography image sequences is presented. This method is based on contrast propagation and involves artery segmentation and motion compensation. The segmentation of coronary arteries is based on the fuzzy connectedness theory and mathematical morphology. Points of correspondence between blood vessels are determined using two successive frames based on the minimization of deformation measurements between the open curves. The cost function considers the displacement vector of corresponding matched points and curvature information. Propagation of the contrast material bolus is represented in a parametric image of corrected distance as a function of time. From the parametric image, the instantaneous velocity can be calculated. The proposed methodology was assessed through simulations with synthetic images, images obtained from in-vitro assays and coronary X-ray angiographic images.

Imaging through Diffusing Media by Image Parametric Amplification

Abstract: Imaging through thick diffusing media requires selection of the least scattered light, because ballistic light is only transmitted up to a few millimeters. Hence, temporal gating, i.e. isolation of the front part of a femto or a picosecond pulse appears as a promising tool to form images of objects embedded in thick media, like tumors in human breast. We have used parametric image amplification to obtain images with a time gate duration of about 20 ps. At first, we used latex beads solutions, whose diffusing properties are well known, to characterize the method and its dynamic range for selection of the ballistic light. In a second step, objects embedded in biological tissues, like chicken meat, were imaged. The best results have been obtained by forming the image without lenses, by exploiting the fact that the idler is phase-conjugated with respect to the signal in the transverse directions, while it propagates forward. A 1 cm3 piece of liver embedded in a 4 cm thick chicken breast tissue has been detected.