A constrained dual-energy reconstruction method for material-selective transmission tomography

A new reconstruction method has been developed for material-selective tomography that allows non-negativity and maximum density constraints to be enforced on each pixel. In addition, uncertainty in the projection data is appropriately accounted for. Results of applying the constrained reconstruction to simulated data demonstrate significant improvements over unconstrained reconstructions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31121/1/0000017.pd

Regularized Emission Image Reconstruction Using Imperfect Side Information

A spatially variant penalized-likelihood method for tomographic image reconstruction based on a weighted Gibbs penalty was investigated. The penalty weights are determined from structural side information, such as the locations of anatomical boundaries in high-resolution magnetic resonance images. Such side information will be imperfect in practice, and a simple simulation demonstrated the importance of accounting for the errors in boundary locations. Methods are discussed for prescribing the penalty weights when the side information is noisy. Simulation results suggest that even imperfect side information is useful for guiding spatially variant regularization.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85869/1/Fessler110.pd

Robust Maximum- Likelihood Position Estimation in Scintillation Cameras

The classical maximum-likelihood (ML) estimator for the position of a scintillation event in a gamma camera, as derived by Gray and Macovski in 1976, requires exact knowledge of the light-spread function (LSF) of each photomultiplier tube. In practice, one must determine each LSF from noisy measurements corrupted by Poisson noise, quantization error, and electronic noise and bias. Since the ML position estimator involves derivatives of each LSF, even small measurement errors can result in degraded estimator performance. In this paper we derive a robust ML position estimator that accounts for the statistical uncertainty in LSF measurements. The form of the robust estimator diminishes contributions from the tails of the LSF, where the relative measurement errors are the largest.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85879/1/Fessler117.pd

Design of a very high-resolution small animal PET scanner using a silicon scatter detector insert

A small animal positron emission tomography (PET) instrument using a high-resolution solid-state detector insert in a conventional PET system was investigated for its potential to achieve sub-millimeter spatial resolution for mouse imaging. Monte Carlo simulations were used to estimate the effect of detector configurations (thickness, length and radius) on sensitivity. From this initial study, a PET system having an inner cylindrical silicon detector (4 cm ID, 4 cm length and 1.6 cm thickness composed of 16 layers of 300 µm × 300 µm × 1 mm pads), for scattering, surrounded by an outer cylindrical BGO scintillation detector (17.6 cm ID, 16 cm length and 2 cm thickness segmented into 3 mm × 3 mm × 20 mm crystals), for capture was evaluated in detail. In order to evaluate spatial resolution, sensitivity and image quality of the PET system, 2D images of multiple point and cylinder sources were reconstructed with the simulation data including blurring from positron range and annihilation photon acollinearity using filtered backprojection (FBP). Simulation results for 18F demonstrate 340 µm FWHM at the center of the field of view with 1.0% sensitivity from the coincidence of single scattering events in both silicon detectors and 1.0 mm FWHM with 9.0% sensitivity from the coincidence of single scattering in the silicon and full energy absorption of the second photon in the BGO detector.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58095/2/pmb7_15_019.pd

Maximum-Likelihood Dual-Energy TomographicImage Reconstruction

Dual-energy (DE) X-ray computed tomography (CT) has shown promise for material characterization and for providing quantitatively accurate CT values in a variety of applications. However, DE-CT has not been used routinely in medicine to date, primarily due to dose considerations. Most methods for DE-CT have used the filtered backprojection method for image reconstruction, leading to suboptimal noise/dose properties. This paper describes a statistical (maximum-likelihood) method for dual-energy X-ray CT that accommodates a wide variety of potential system configurations and measurement noise models. Regularized methods (such as penalized-likelihood or Bayesian estimation) are straightforward extensions. One version of the algorithm monotonically decreases the negative log-likelihood cost function each iteration. An ordered-subsets variation of the algorithm provides a fast and practical version.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85934/1/Fessler172.pd

Incorporating MRI Region Information into SPECT Reconstruction Using Joint Estimation

Single photon emission computed tomographic images (SPECT) have relatively poor resolution. In an attempt to improve SPECT image quality, many methods have been developed for including anatomic information, extracted from higher resolution, structurally correlated magnetic resonance images (MRI), into the SPECT reconstruction process. These methods provide improved SPECT reconstruction accuracy if the anatomic information is perfectly correlated with the SPECT functional information. However there exist mismatches between MRI anatomical structures and SPECT functional structures due to different imaging mechanisms. It has been reported that if the MR structures are applied into SPECT, the mismatched part will cause artifacts. The paper describes a joint estimation approach which unifies MR information extraction and SPECT reconstruction processes to avoid these artifacts. Both qualitative and quantitative evaluations show that the method improves the SPECT reconstruction where the MR information matches and is robust to mismatched MR information.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86029/1/Fessler134.pd

Experimental Evaluation For Joint Estimation Approach

Single photon emission computed tomography (SPECT) provides a potential to perform in vivo quantification of the radioactivity and dose distributions in the process of evaluating radiopharmaceuticals. The inherent modest resolution in SPECT impedes the potential of accurate quantification. Previously, the authors investigated a joint estimation approach for combining SPECT functional information with high resolution, structurally correlated MRI anatomical information to improve the accuracy of SPECT quantification, and the computer simulation results showed that this approach can exploit MRI region information that matches the SPECT functional information and to reduce artifacts caused by mismatched MRI anatomical information. Here, the authors further describe the experimental evaluation of the joint estimation approach using actual SPECT and MRI imaging with an animal-sized phantom. They describe practical details in applying the joint estimation approach and present the experimental evaluation results of quantitative analysis.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86000/1/Fessler144.pd

Improved Modeling of System Response in List Mode EM Reconstruction of Compton Scatter Camera Images

An improved List Mode EM method for reconstructing Compton scattering camera images has been developed. First, an approximate method for computation of the spatial variation in the detector sensitivity has been derived and validated by Monte Carlo computation. A technique for estimating the relative weight of system matrix coefficients for each gamma in the list has also been employed, as has a method for determining the relative probabilities of emission having some from pixels tallied in each list-mode back-projection. Finally, a technique has been developed for modeling the effects of Doppler broadening and finite detector energy resolution on the relative weights for pixels neighbor to those intersected by the back-projection, based on values for the FWHM of the spread in the cone angle computed by Monte Carlo. Memory issues typically associated with list mode reconstruction are circumvented by storing only a list of the pixels intersected by the back-projections, and computing the weights of the neighboring pixels at each iteration step. Simulated projection data has been generated for a representative Compton camera system (CSPRINT) for several source distributions and reconstructions performed. Reconstructions have also been performed for experimental data for distributed sources.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86027/1/Fessler157.pd

Joint Estimation for Incorporating MRI Anatomic Images into SPECT Reconstruction

To improve SPECT reconstruction using spatially-correlated magnetic resonance (MR) images as a source of side information, one must account for mismatch between MRI anatomical information and SPECT functional information. The authors investigate an approach which incorporates the anatomical information into SPECT reconstruction by using region labels representing the anatomical regions extracted from MRI. Each SPECT pixel corresponds to one region label. Both SPECT pixel mean intensities and region labels are jointly estimated by a penalized Maximum-Likelihood criterion using an iterative Space-Alternating Generalized EM algorithm. The likelihood function incorporates both the SPECT noise distribution and the MRI side information measurement statistics. Since the region labels are estimated jointly from both segmented MRI and SPECT projection data, only those anatomical regions that match SPECT functional regions are represented by the estimated labels, and are used to constrain the SPECT reconstruction. The artifacts due to the mismatched MR anatomical region information are reduced using joint estimation. By comparing image quality and the Bias vs. Variance tradeoffs, the authors see that the joint estimation has the potential to improve the SPECT estimation result.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85806/1/Fessler129.pd

Fast Parallelizable Algorithms for Transmission Image Reconstruction

Presents a new class of algorithm for penalized-likelihood reconstruction of attenuation maps from low-count transmission scans. The authors derive the algorithms by applying to the transmission log-likelihood a variation of the convexity technique developed by De Pierro for the emission case. The new algorithms overcome several limitations associated with previous algorithms. (1) Fewer exponentiations are required than in the transmission EM algorithm or in coordinate-ascent algorithms. (2) The algorithms intrinsically accommodate nonnegativity constraints, unlike many gradient-based methods. (3) The algorithms are easily parallelizable, unlike coordinate-ascent algorithms and perhaps line-search algorithms. The authors show that the algorithms converge faster than several alternatives, even on conventional workstations. They give examples from low-count PET transmission scans and from truncated fan-beam SPECT transmission scans.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86006/1/Fessler136.pd