arXiv subjects

Craig S. Levin

Publications and source records attributed to Craig S. Levin.

5 recordsLinked to original sources

arXiv2026

Alkaline-Earth Rare-Earth Fluoride Nanoparticle Superlattices for Ultrafast, Radiation Stable Scintillators

Radioluminescent nanostructures provide a pathway to the fabrication of next-generation scintillators with tunability in composition, size, and morphology, and spectral and temporal properties, as well as scalable processing. Here we create a 3D millimeter-scale solid-state scintillators from SrLuF Ce3+, Pr3+ (SrLuF) core-shell nanostructures, integrating nanoscale building blocks into self-assembled macroscopic crystals. These scintillators exhibit single-digit nanosecond decay times, linear response, resistance to radiation-induced degradation, and optical emission yields within an order of magnitude of YAG Ce3+. We select a SrLuF host lattice owing to its high effective atomic number, wide band gap, and low phonon energy, which together support efficient 4f-5d radiative transitions from Ce3+ and Pr3+ activators while suppressing afterglow. We create a library of core-shell nanoscintillators with undoped SrLuF shells and cores spanning compositions from undoped SrLuF to fully doped SrCeF or SrPrF. Time-resolved and steady-state X-ray excited optical luminescence (XEOL) reveal broadband emission at 310 nm (Ce3+) and 335 nm (Pr3+) with biexponential decays in the sub-nanosecond (100-500 ps) and sub-15 ns (4-13 ns) regimes, demonstrating tunable radiative efficiency and ultrafast dynamics. Ensemble performance of the mm-scale superlattices is characterized under both continuous-wave and femtosecond high-intensity excitation, revealing high light yield, linear response, and radiation hardness under extreme irradiation of ultrafast 50fs X-ray pulses up to 5mJ per mm2 corresponding to a peak intensity of 1013 W per cm2. Together, these results establish a design framework for stable, bright, and tunable scintillation platforms with applications in precision health, space exploration and hard X-ray imaging at next-generation free-electron laser facilities.

cond-mat.mtrl-sci↗

arXiv2026

Maximum Likelihood Estimation Yields Accurate Line-of-Response Assignment for Positron + Prompt Gamma Ray Events in Multiplexed PET (mPET)

For accurate disease characterization using positron emission tomography (PET), it is desirable to image multiple radiotracers in a single scan. Conventional PET methods cannot do this due to the indistinguishable annihilation photons produced by different radiotracers. One approach is to label one radiotracer with a positron+prompt-gamma ($\beta^+\!\!-\!\!\gamma$) isotope producing triple coincidences, and another with a pure positron-emitting ($\beta^+$) isotope producing double coincidences. However, $\beta^+\!\!-\!\!\gamma$ emitters present challenges in correctly identifying the two annihilation photons, or equivalently, assigning the correct line-of-response (LOR) to triple-photon coincidence events. Here, we propose a maximum likelihood estimation (MLE) framework leveraging spatial, timing, and energy information to determine the most probable LOR. Simulation studies validated the method: simulations showed over 96\% and 94\% accuracy for LOR assignment of $\beta^+\!\!-\!\!\gamma$ emitters $^{22}$Na and $^{124}$I point sources, respectively. Furthermore, simulated phantom imaging of $^{22}$Na or $^{124}$I distributions alongside a $\beta^+$ emitter demonstrated that MLE LOR assignment achieved comparable image quality -- measured by contrast recovery coefficient (CRC) and cross-talk ratio (XR) -- to benchmark methods, where the prompt gamma was identified using an energy threshold ($\geq 650$ keV) for $^{22}$Na and as the highest-energy photon for $^{124}$I.

physics.med-ph↗

arXiv2024

Comparison of Deep Learning and Particle Smoother EM Methods for Estimation of Rb-82 Myocardial Perfusion PET Kinetic Parameters

Positron emission tomography (PET) enables quantification of dynamic physiological processes through time-resolved imaging. In Rb-82 myocardial perfusion PET, kinetic compartment modeling is used to estimate physiological parameters and derive myocardial blood flow. However, conventional nonlinear least squares (NLLS) estimation is sensitive to model misspecification when not all parameters can be reliably estimated and must instead be fixed or initialized using population averages, which can degrade accuracy. This work develops and evaluates two alternative kinetic analysis approaches for Rb-82 PET: a particle smoother-based Expectation-Maximization method (PSEM) and a convolutional neural network (CNN). Both methods were evaluated using simulated Rb-82 dynamic myocardial perfusion studies and compared against NLLS and a Kalman smoother-based Expectation-Maximization (KEM) algorithm across multiple frame durations and noise levels. Across 2-10 s frames, the CNN achieved the lowest relative errors for all parameters (F: 8.78-4.98%, k3: 26.05-25.50%, k4: 34.34-22.76%), significantly outperforming NLLS, KEM, and PSEM (Holm-adjusted p < 1e-15 at 1.0x noise, 2 s frames), although performance degraded under out-of-distribution input-function conditions. Overall, the CNN provided the most accurate and robust in-distribution kinetic parameter estimates across frame durations. In contrast, PSEM exhibited parameter-dependent behavior, improving k3 estimation while underperforming for F, suggesting that further methodological refinement is needed.

physics.med-ph↗

arXiv2021

Virtual Point Source Synthesis method for 3D Scintillation Detector Characterization

A novel data-processing method was developed to facilitate scintillation detector characterization. Combined with fan-beam calibration, this method can be used to quickly and conveniently calibrate gamma-ray detectors for SPECT, PET, homeland security or astronomy. Compared with traditional calibration methods, this new technique can accurately calibrate a photon-counting detector, including DOI information, with greatly reduced time. The enabling part of this technique is fan-beam scanning combined with a data-processing strategy called the common-data subset (CDS) method, which was used to synthesize the detector's mean detector response functions (MDRFs). Using this approach, $2N$ scans ($N$ in x and $N$ in y direction) are necessary to finish calibration of a 2D detector as opposed to $N^2$ scans with a pencil beam. For a 3D detector calibration, only $3N$ scans are necessary to achieve the 3D detector MDRFs that include DOI information. Moreover, this calibration technique can be used for detectors with complicated or irregular MDRFs. We present both Monte-Carlo simulations and experimental results that support the feasibility of this method.

physics.ins-det↗

arXiv2018

Positioning of Multiple Photon Interaction Events in Cross Strip Cadmium Zinc Telluride Detectors for PET

This report summarizes work done during PhD rotation that proposes an algorithm that uses anode- cathode trigger time difference and cathode to anode pulse height ratio to resolve photon event positioning degeneracy in a novel Cadmium Zinc Telluride (CZT) photon detector for positron emission tomography (PET). The detectors used comprise 40 mm x 40 mm x 5 mm monolithic CZT crystals that employ a cross-strip electrode pattern with interspersed steering electrodes to obtain high spatial and energy resolution. The specific positioning degeneracy studied results when a photon event interacts in two detector pixels, triggering two anode and two cathode strips, hence presenting four pixels as potential interaction locations. An experiment was performed where a 1 mm diameter collimated pencil beam of annihilation photons was used to target a detector pixel of known location. The data acquired provided an empirical basis to train and test the algorithm. The study shows that, depending on the restrictions applied on the data set, the proposed algorithm accurately identifies the true photon interaction locations 59.7% to 66.7% of the time, which is 19.4% to 33.4% better than an unbiased Bernoulli trial. Further improvements of the algorithm will enhance the effective system photon sensitivity by extracting useful information from events which would otherwise be discarded.

physics.med-ph↗