Higher-spin strings and W minimal models

We study the spectrum of physical states for higher-spin generalisations of string theory, based on two-dimensional theories with local spin-2 and spin-$s$ symmetries. We explore the relation of the resulting effective Virasoro string theories to certain $W$ minimal models. In particular, we show how the highest-weight states of the $W$ minimal models decompose into Virasoro primaries.Comment: 13 pages, CTP TAMU-43/93, KUL-TF-93/9

Polyaniline- and poly(ethylenedioxythiophene)-cellulose nanocomposite electrodes for supercapacitors

The formation and characterisation of films of polyaniline (PANI) and poly(ethylenedioxythiophene) (PEDOT) containing cellulose nanocrystals (CNXLs) from cotton are described. PANI/CNXL films were electrodeposited from a solution containing CNXLs, HCl and aniline, while PEDOT/CNXL films were electrodeposited from a solution containing CNXLs, lithium perchlorate and ethylenedioxythiophene. In each case, incorporation of CNXLs into the electrodepositing polymer film led to the formation of a porous polymer/CNXL nanocomposite structure. The films were characterised using scanning electron microscopy, cyclic voltammetry, electrochemical impedance spectroscopy (EIS) and galvanostatic charge-discharge analysis. The specific capacitances of the nanocomposite materials were higher than those of the CNXL-free counterparts (488 F/g for PANI/CNXL; 358 F/g for PANI; 69 F/g for PEDOT/CNXL; 58 F/g for PEDOT). The durability of the PANI/CNXL film under potential cycling was slightly better than that of the CNXL-free PANI, while the PEDOT film was slightly more durable than the PEDOT/CNXL film. Using electrodeposition, it was possible to form thick PANI/CNXL films, with total electrode capacitances of 2.07 F farads per squared cm (and corresponding specific capacitances of 440 F/g), demonstrating that this particular nanocomposite may be promising for the construction of high performance supercapacitors

Improved PET/CT Respiratory Motion Compensation by Incorporating Changes in Lung Density

Positron emission tomography/computed tomography (PET/CT) lung imaging is highly sensitive to motion. Although several techniques exist to diminish motion artifacts, a few accounts for both tissue displacement and changes in density due to the compression and dilation of the lungs, which cause quantification errors. This article presents an experimental framework for joint activity image reconstruction and motion estimation in PET/CT, where the PET image and the motion are directly estimated from the raw data. Direct motion estimation methods for motion-compensated PET/CT are preferable as they require a single attenuation map only and result in optimal signal-to-noise ratio (SNR). Previous implementations, however, failed to address changes in density during respiration. We propose to account for such changes using the Jacobian determinant of the deformation fields. In a feasibility study, we demonstrate on a modified extended cardiac-torso (XCAT) phantom with breathing motion-where the lung density and activity vary-that our approach achieved better quantification in the lungs than conventional PET/CT joint activity image reconstruction and motion estimation that does not account for density changes. The proposed method resulted in lower bias and variance in the activity images, reduced mean relative activity error in the lung at the reference gate (-4.84% to -3.22%) and more realistic Jacobian determinant values

Challenges in Optimization of a Stationary Tomographic Molecular Breast Imaging System

A prototype Molecular Breast Imaging (MBI) system is currently under development, motivated by the need of a practical low-dose system for use in patients with dense breast tissue, where conventional mammography is limited. The system is based on dual opposing CZT detector arrays and multi-pinhole collimators which allow for multiplexing in the projection data. We have performed optimization of various design parameters based on either contrast-to-noise ratio (CNR) in the reconstructed images or area under the localization receiver operating characteristics curve (LROC-AUC) obtained using the scan statistic model. The optimizations were based on simulated data, and the parameters investigated were pinhole size and opening angle, pinhole separation and collimator-to-detector separation. The two optimization approaches resulted in similar design parameters, allowing for reconstruction of tomographic images with high CNR and lesion detectability, which can lead to a reduced dose or scan time as compared to planar MBI

Design of an Ultra-low-dose, Stationary, Tomographic Molecular Breast Imaging System

Molecular Breast Imaging (MBI) has been shown to have high sensitivity in detection of cancer, even in patients with dense breasts where conventional mammography has issues. However the technique has limited acceptance due to the relatively high radiation dose and long imaging time. Improved lesion detection can be achieved using tomography, however this normally involves detector motion and complex mechanics. Our goal is to develop a low-dose stationary tomographic MBI system with similar or better sensitivity for lesion detection to conventional planar MBI. The proposed system utilizes state-of-the-art cadmium zinc telluride (CZT) detectors based on 2mm pixels, with sub-pixelization and depth of interaction (DOI) capability, combined with densely packed multi-pinhole collimators. Use of closely-spaced pinholes improves efficiency and angular sampling, but results in significant multiplexing. De-multiplexing algorithms have been developed that take advantage of the DOI acquisition to achieve tomographic reconstruction using two opposing planar detectors which apply mild compression to the breast. Simulation studies of multiple lesions with clinically realistic contrast have been used to demonstrate the feasibility of the design and to characterize the expected performance. Reconstruction without de-multiplexing resulted in significant artefacts. De-multiplexing without DOI had limited success but with DOI resulted in artefact-free images, with good contrast and axial plane definition. Lesion detectability was preserved even with reduction of acquisition time (or radiation dose) by a factor of 4. Further optimization has potential for even greater dose reduction. A prototype system is currently being constructed to validate these findings

A New Concept for a Low-Dose Stationary Tomographic Molecular Breast Imaging Camera Using 3D Position Sensitive CZT Detectors

Pixelated CZT detectors have been used in a variety of molecular imaging applications for many years. The interplay of gamma camera and collimator geometric design, gantry motion, and image reconstruction determines the image quality and dose-time-FOV trade-offs. In particular, Molecular Breast Imaging (MBI) has been shown to provide excellent diagnostic results in patients with dense breast tissue, but higher than mammography patient dose and long imaging time impede its wide adoption. We propose a new transformative system concept combining the advantages of CZT detectors (superior energy and position resolution and depth of interaction sensing), multi-pinhole collimation and novel image reconstruction to mitigate those drawbacks without compromising diagnostic content. The closely spaced pinholes allow tomographic image reconstruction, improve sensitivity and angular sampling, but result in significant multiplexing. Novel de-multiplexing algorithms have been developed to mitigate the adverse multiplexing artefacts using the DOI. GATE simulations of the new camera demonstrate a potential to reduce the patient dose by at least a factor of 5 in comparison to planar MBI, thus reducing the dose to the level of an average mammography scan. The first prototype has been built at Kromek with 3D position sensitive CZT detectors and is being evaluated using an "activity-painting"setup with a point 57Co source. Initial results demonstrate the expected performance improvement with the use of sub-pixelisation and DOI. The next steps of the development will include accurate evaluation of the image quality and the dose reduction followed by building a larger scale clinical prototype using optimised detector design

Performance evaluation of MAP algorithms with different penalties, object geometries and noise levels

A new algorithm (LBFGS-B-PC) which combines ideas of two existing convergent reconstruction algorithms, relaxed separable paraboloidal surrogate (SPS) and limited-memory Broyden-Fletcher-Goldfarb-Shanno with boundary constraints (LBFGS-B), is proposed. Its performance is evaluated in terms of log-posterior value and regional recovery ratio. The results demonstrate the superior convergence speed of the proposed algorithm to relaxed SPS and LBFGS-B, regardless of the noise level, activity distribution, object geometry, and penalties

Integrable Supersymmetry Breaking Perturbations of N=1,2 Superconformal Minimal Models

We display a new integrable perturbation for both N=1 and N=2 superconformal minimal models. These perturbations break supersymmetry explicitly. Their existence was expected on the basis of the classification of integrable perturbations of conformal field theories in terms of distinct classical KdV type hierarchies sharing a common second Hamiltonian structure.Comment: 10 pages (harvmac), LAVAL PHY-20-9

Performance improvement and validation of a new MAP reconstruction algorithm

We previously proposed a fast maximum a posteriori (MAP) algorithm, limited-memory Broyden-Fletcher-Goldfarb- Shanno with boundary constrains (LBFGS-B-PC), combining LBFGS-B with diagonal preconditioning. Previous results have shown in simulations that it converges using around 40 projections independent of many factors. The aim of this study is to improve the algorithm further by using a better initial image and a modified preconditioner that is less sensitive to noise and data scale. By initializing the algorithm with the best initial image (one full iteration of OSEM with 35 subsets), ROI values can converge almost twice as fast for the same computation time. Moreover, the new preconditioner makes the performance more consistent between high and low count data sets. In addition, we have found a means to choose the stopping criteria to reach a desired level of quantitative accuracy in the reconstructed image. Based on the results with patient data, the optimized LBFGS-B-PC shows promise for clinical imaging