Accurate system modeling in tomographic image reconstruction has been shown to reduce the spatial variance of resolution and improve quantitative accuracy. System modeling can be improved through analytic calculations, Monte Carlo simulations, and physical measurements. The purpose of this work is to improve clinical fully-3-D reconstruction without substantially increasing computation time. We present a practical method for measuring the detector blurring component of a whole-body positron emission tomography (PET) system to form an approximate system model for use with fully-3-D reconstruction. We employ Monte Carlo simulations to show that a non-collimated point source is acceptable for modeling the radial blurring present in a PET tomograph and we justify the use of a Na22 point source for collecting these measurements. We measure the system response on a whole-body scanner, simplify it to a 2-D function, and incorporate a parameterized version of this response into a modified fully-3-D OSEM algorithm. Empirical testing of the signal versus noise benefits reveal roughly a 15% improvement in spatial resolution and 10% improvement in contrast at matched image noise levels. Convergence analysis demonstrates improved resolution and contrast versus noise properties can be achieved with the proposed method with similar computation time as the conventional approach. Comparison of the measured spatially variant and invariant reconstruction revealed similar performance with conventional image metrics. Edge artifacts, which are a common artifact of resolution-modeled reconstruction methods, were less apparent in the spatially variant method than in the invariant method. With the proposed and other resolution-modeled reconstruction methods, edge artifacts need to be studied in more detail to determine the optimal tradeoff of resolution/contrast enhancement and edge fidelity.

The addition of accurate system modeling in PET image reconstruction results in images with distinct noise texture and characteristics. In particular, the incorporation of point spread functions (PSF) into the system model has been shown to visually reduce image noise, but the noise properties have not been thoroughly studied. This work offers a systematic evaluation of noise and signal properties in different combinations of reconstruction methods and parameters. We evaluate two fully 3D PET reconstruction algorithms: (1) OSEM with exact scanner line of response modeled (OSEM+LOR), (2) OSEM with line of response and a measured point spread function incorporated (OSEM+LOR +PSF), in combination with the effects of four post-reconstruction filtering parameters and 1-10 iterations, representing a range of clinically acceptable settings. We used a modified NEMA image quality (IQ) phantom, which was filled with 68 Ge and consisted of six hot spheres of different sizes with a target/background ratio of 4:1. The phantom was scanned 50 times in 3D mode on a clinical system to provide independent noise realizations. Data were reconstructed with OSEM+LOR and OSEM+LOR+PSF using different reconstruction parameters, and our implementations of the algorithms match the vendor's product algorithms. With access to multiple realizations, background noise characteristics were quantified with four metrics. Image roughness and the standard deviation image measured the pixel-to-pixel variation; background variability and ensemble noise quantified the region-to-region variation. Image roughness is the image noise perceived when viewing an individual image. At matched iterations, the addition of PSF leads to images with less noise defined as image roughness (reduced by 35% for unfiltered data) and as the standard deviation image, while it has no effect on background variability or ensemble noise. In terms of signal to noise performance, PSF-based reconstruction has a 7% improvement in contrast recovery at matched ensemble noise levels and 20% improvement of quantitation SNR in unfiltered data. In addition, the relations between different metrics are studied. A linear correlation is observed between background variability and ensemble noise for all different combinations of reconstruction methods and parameters, suggesting that background variability is a reasonable surrogate for ensemble noise when multiple realizations of scans are not available.

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Organic light‐emitting diodes (OLEDs) can promise flexible, light weight, energy conservation, and many other advantages for next‐generation display and lighting applications. However, achieving efficient blue electroluminescence still remains a challenge. Though both phosphorescent and thermally activated delayed fluorescence materials can realize high‐efficiency via effective triplet utilization, they need to be doped into appropriate host materials and often suffer from certain degree of efficiency roll‐off. Therefore, developing efficient blue‐emitting materials suitable for nondoped device with little efficiency roll‐off is of great significance in terms of practical applications. Herein, a phenanthroimidazole−anthracene blue‐emitting material is reported that can attain high efficiency at high luminescence in nondoped OLEDs. The maximum external quantum efficiency (EQE) of nondoped device is 9.44% which is acquired at the luminescence of 1000 cd m−2. The EQE is still as high as 8.09% even the luminescence reaches 10 000 cd m−2. The maximum luminescence is ≈57 000 cd m−2. The electroluminescence (EL) spectrum shows an emission peak of 470 nm and the Commission International de L'Eclairage (CIE) coordinates is (0.14, 0.19) at the voltage of 7 V. To the best of the knowledge, this is among the best results of nondoped blue EL devices.

Herein, a simple aza-aromatic compound dibenzo[a,c]phenazine (DPPZ), which exhibits single-molecule white light with a ternary emission, consisting of simultaneous fluorescence (S 1 →S 0 ) and dual room-temperature phosphorescence (RTP, T 2 →S 0 and T 1 →S 0 ) is reported. The Commission Internationale de l' Éclairage coordinates of DPPZ powder are (0.28, 0.33). To everyone's knowledge, this is the first case to achieve single-molecule white emission with ternary emission of fluorescence and dual RTP. This finding provides a prototype strategy to realize low-cost, stable pure organic singlemolecule white light emission with three standard primary colors through further precise modulation of excited states.

PET is a medical imaging modality with proven clinical value for disease diagnosis and treatment monitoring. The integration of PET and CT on modern scanners provides a synergy of the two imaging modalities. Through different mathematical algorithms, PET data can be reconstructed into the spatial distribution of the injected radiotracer. With dynamic imaging, kinetic parameters of specific biological processes can also be determined. Numerous efforts have been devoted to the development of PET image reconstruction methods over the last four decades, encompassing analytic and iterative reconstruction methods. This article provides an overview of the commonly used methods. Current challenges in PET image reconstruction include more accurate quantitation, TOF imaging, system modeling, motion correction and dynamic reconstruction. Advances in these aspects could enhance the use of PET/CT imaging in patient care and in clinical research studies of pathophysiology and therapeutic interventions. Keywordsanalytic reconstruction; fully 3D imaging; iterative reconstruction; maximum-likelihood expectation-maximization method; PET PET is a medical imaging modality with proven clinical value for the detection, staging and monitoring of a wide variety of diseases. This technique requires the injection of a radiotracer, which is then monitored externally to generate PET data [1,2]. Through different algorithms, PET data can be reconstructed into the spatial distribution of a radiotracer. PET imaging provides noninvasive, quantitative information of biological processes, and such functional information can be combined with anatomical information from CT scans. The integration of PET and CT on modern PET/CT scanners provides a synergy of the two imaging modalities, and can lead to improved disease diagnosis and treatment monitoring [3,4].Considering that PET imaging is limited by high levels of noise and relatively poor spatial resolution, numerous research efforts have been devoted to the development and improvement of PET image reconstruction methods since the introduction of PET in the 1970s. This article provides a brief introduction to tomographic reconstruction and an overview of the commonly used methods for PET. We start with the problem formulation and then introduce data correction methods. We then proceed with reconstruction methods

Random walks constitute a fundamental mechanism for a large set of dynamics taking place on networks. In this article, we study random walks on weighted networks with an arbitrary degree distribution, where the weight of an edge between two nodes has a tunable parameter. By using the spectral graph theory, we derive analytical expressions for the stationary distribution, mean first-passage time (MFPT), average trapping time (ATT), and lower bound of the ATT, which is defined as the average MFPT to a given node over every starting point chosen from the stationary distribution. All these results depend on the weight parameter, indicating a significant role of network weights on random walks. For the case of uncorrelated networks, we provide explicit formulas for the stationary distribution as well as ATT. Particularly, for uncorrelated scale-free networks, when the target is placed on a node with the highest degree, we show that ATT can display various scalings of network size, depending also on the same parameter. Our findings could pave a way to delicately controlling random-walk dynamics on complex networks.

Hole transporting materials (HTMs) play a crucial role in achieving highly efficient and stable perovskite solar cells (PSCs). Spirotyped materials being the most widely used HTMs are commonly utilized with dopants, such as Li-TFSI, to improve their carrier mobility significantly. However, dopants could affect the morphology of hole transporting layer negatively by forming defects and pinholes which restrict the performance of devices. Here, we adopt the extended πconjugated structures N-ethylcarbazole and dibenzothiophene to substitute the donor group 4-methoxyphenyl of spiro-OMeTAD, devising two novel HTMs, SC and ST, respectively. Notably, SC possesses low crystallinity and good solubility due to the existence of ethyl in side groups, leading to decent miscibility with Li-TFSI to prevent unfavorable phase-separation. The SC-based device delivers the best power conversion efficiency (PCE) of 21.76% which is higher than that of spiro-OMeTAD (20.73%), attributed to the formation of smooth and pinhole-free morphology. Moreover, it exhibits long-term stability and retains over 90% of initial PCE value for more than 30 days without encapsulation in ambient air. In contrast, the STbased device suffers from dense pinholes induced by its relatively high crystallinity and poor solubility, resulting in a low PCE of 18.18% and inferior stability. Thus, it is effective to modify the side groups in spiro-typed HTMs with specific structures to obtain predictable properties, fabricating PSCs with high efficiency and stability facilely.