Tethered Helical Ladder-Type Aromatic Lactams.

Tethered nonplanar aromatics (TNAs) make up an important class of nonplanar aromatic compounds showing unique features. However, the knowledge on the synthesis, structures, and properties of TNAs remains insufficient. In this work, a new type of TNAs, the tethered aromatic lactams, is synthesized via Pd-catalyzed consecutive intramolecular direct arylations. These molecules possess a helical ladder-type conjugated system of up to 13 fused rings. The overall yields ranged from 3.4 to 4.3%. The largest of the tethered aromatic lactams, 6L-Bu-C14, demonstrates a guest-adaptive hosting capability of TNAs for the first time. When binding fullerene guests, the cavity of 6L-Bu-C14 became more circular to better accommodate spherical fullerene molecules. The host-guest interaction is thoroughly studied by X-ray crystallography, theoretical calculations, fluorescence titration, and nuclear magnetic resonance (NMR) titration experiments. 6L-Bu-C14 shows stronger binding with C70 than with C60 due to the better convex-concave π-π interaction. P and M enantiomers of all tethered aromatic lactams show distinct and persistent chiroptical properties and demonstrate the potential of chiral TNAs as circularly polarized luminescence (CPL) emitters.

Carbon quantum dots modified and Y3+ doped Ni3(NO3)2(OH)4 nanospheres with excellent battery-like supercapacitor performance.

Supercapacitor is an important energy storage device widely used in the automobile industry, military production, and communication equipment because of its fast charge-discharge rate, and high power density. Herein, carbon quantum dots modified and Y3+ doped Ni3(NO3)2(OH)4 (NiY@CQDs) nanospheres are prepared by a solvothermal method and used as an electrode material. The electrochemical properties of NiY@CQDs were measured in a three-electrode system. An asymmetric supercapacitor (ASC) cell was assembled with activated carbon (AC) as the anode and NiY@CQDs as the cathode. The electrochemical properties of the ASC device were measured in a two-electrode system. Experimental results show the shape of NiY@CQDs is petal-shaped and the introducing carbon quantum dots and doping Y3+ significantly increases the specific surface area, conductivity, and specific capacitance of Ni3(NO3)2(OH)4. The mass-specific capacitance of NiY@CQDs reaches up to 2944 F g-1 at a current density of 1 A g-1. The asymmetric supercapacitor of NiY@CQDs//AC has a high energy density of 138.65 Wh kg-1 at a power density of 1500 W kg-1, displaying a wide range of application prospects in the energy storage area.

MOF-derived NiAl2O4/NiCo2O4 porous materials as supercapacitors with high electrochemical performance.

Metal-organic framework compounds are extensively utilized in various fields, such as electrode materials, owing to their distinctive porous structure and significant specific surface area. In this study, NiCoAl-MOF metal-organic framework precursors were synthesized by a solvothermal method, and NiAl2O4/NiCo2O4 electrode materials were prepared by the subsequent calcination of the precursor. These materials were characterized by XRD, XPS, BET tests, and SEM, and the electrochemical properties of the electrode materials were tested by CV and GCD methods. BET tests showed that NiAl2O4/NiCo2O4 has an abundant porous structure and a large specific surface area of up to 105 m2 g-1. The specific capacitance of NiAl2O4/NiCo2O4 measured by the GCD method reaches up to 2870.83 F g-1 at a current density of 1 A g-1. The asymmetric supercapacitor NiAl2O4/NiCo2O4//AC assembled with activated carbon electrodes has a maximum energy density of 166.98 W h kg-1 and a power density of 750.00 W kg-1 within a voltage window of 1.5 V. In addition, NiAl2O4/NiCo2O4 materials have good cycling stability. These advantages make it a good candidate for the application of high-performance supercapacitors.

Increasing angular sampling through deep learning for stationary cardiac SPECT image reconstruction.

BACKGROUND: The GE Discovery NM (DNM) 530c/570c are dedicated cardiac SPECT scanners with 19 detector modules designed for stationary imaging. This study aims to incorporate additional projection angular sampling to improve reconstruction quality. A deep learning method is also proposed to generate synthetic dense-view image volumes from few-view counterparts. METHODS: By moving the detector array, a total of four projection angle sets were acquired and combined for image reconstructions. A deep neural network is proposed to generate synthetic four-angle images with 76 ([Formula: see text]) projections from corresponding one-angle images with 19 projections. Simulated data, pig, physical phantom, and human studies were used for network training and evaluation. Reconstruction results were quantitatively evaluated using representative image metrics. The myocardial perfusion defect size of different subjects was quantified using an FDA-cleared clinical software. RESULTS: Multi-angle reconstructions and network results have higher image resolution, improved uniformity on normal myocardium, more accurate defect quantification, and superior quantitative values on all the testing data. As validated against cardiac catheterization and diagnostic results, deep learning results showed improved image quality with better defect contrast on human studies. CONCLUSION: Increasing angular sampling can substantially improve image quality on DNM, and deep learning can be implemented to improve reconstruction quality in case of stationary imaging.

Zero-Dimensional Hybrid Antimony Chloride with Near-Unity Broad-Band Orange-Red Emission toward Solid-State Lighting.

Zero-dimensional (0D) hybrid metal halides are attractive owing to their distinctive structure as well as photoluminescence (PL) characteristics. To discover 0D hybrid metal halides with high photoluminescence quantum yield and good stability is of great significance for white light-emitting diodes (LEDs). Herein, a novel hybrid antimony chloride (CTP)2SbCl5 is synthesized, which shows a bright broad-band orange-red emission peaking at 620 nm under the low energy excitation (365 nm), achieving an excellent photoluminescence quantum yield of 96.8%. In addition, (CTP)2SbCl5 shows an additional emission peaking at 470 nm when excited at high energy (323 nm). PL spectra and density functional theory results demonstrate that the observed dual-band emission originates from the singlet and triplet self-trapped excitons confined in isolated [SbCl5]2- square pyramids. Moreover, (CTP)2SbCl5 presents relatively superior air stability, and the PL intensity still maintains 78% of the initial PL intensity when exposed to the air for above 2 weeks. Benefiting from high-efficiency PL emission and good stability of (CTP)2SbCl5, a stable warm white LED device with a 92.3% color rendering index was prepared by coating blue phosphor BaMgAl10O17:Eu2+, green (Sr,Ba)2SiO4:Eu2+, and orange-red (CTP)2SbCl5 on a 365 nm LED chip. This work provides an efficient luminescent material and also demonstrates the potential application of 0D hybrid antimony chloride in solid-state lighting.

Managing Multiple Halide-Related Defects for Efficient and Stable Inorganic Perovskite Solar Cells.

Halide-related surface defects on inorganic halide perovskite not only induce charge recombination but also severely limit the long-term stability of perovskite solar cells. Herein, adopting density functional theory calculation, we verify that iodine interstitials (Ii ) has a low formation energy similar to that of the iodine vacancy (VI ) and is also readily formed on the surface of all-inorganic perovskite, and it is regarded to function as an electron trap. We screen a specific 2,6-diaminopyridine (2,6-DAPy) passivator, which, with the aid of the combined effects from halogen-Npyridine and coordination bonds, not only successfully eliminates the Ii and dissociative I2 but also passivates the abundant VI . Furthermore, the two symmetric neighboring -NH2 groups interact with adjacent halides of the octahedral cluster by forming hydrogen bonds, which further promotes the adsorption of 2,6-DAPy molecules onto the perovskite surface. Such synergetic effects can significantly passivate harmful iodine-related defects and undercoordinated Pb2+ , prolong carrier lifetimes and facilitate the interfacial hole transfer. Consequently, these merits enhance the power-conversion efficiency (PCE) from 19.6 % to 21.8 %, the highest value for this type of solar cells, just as importantly, the 2,6-DAPy-treated CsPbI3-x Brx films show better environmental stability.

Direct and indirect strategies of deep-learning-based attenuation correction for general purpose and dedicated cardiac SPECT.

PURPOSE: Deep-learning-based attenuation correction (AC) for SPECT includes both indirect and direct approaches. Indirect approaches generate attenuation maps (µ-maps) from emission images, while direct approaches predict AC images directly from non-attenuation-corrected (NAC) images without µ-maps. For dedicated cardiac SPECT scanners with CZT detectors, indirect approaches are challenging due to the limited field-of-view (FOV). In this work, we aim to 1) first develop novel indirect approaches to improve the AC performance for dedicated SPECT; and 2) compare the AC performance between direct and indirect approaches for both general purpose and dedicated SPECT. METHODS: For dedicated SPECT, we developed strategies to predict truncated µ-maps from NAC images reconstructed with a small matrix, or full µ-maps from NAC images reconstructed with a large matrix using 270 anonymized clinical studies scanned on a GE Discovery NM/CT 570c SPECT/CT. For general purpose SPECT, we implemented direct and indirect approaches using 400 anonymized clinical studies scanned on a GE NM/CT 850c SPECT/CT. NAC images in both photopeak and scatter windows were input to predict µ-maps or AC images. RESULTS: For dedicated SPECT, the averaged normalized mean square error (NMSE) using our proposed strategies with full µ-maps was 1.20 ± 0.72% as compared to 2.21 ± 1.17% using the previous direct approaches. The polar map absolute percent error (APE) using our approaches was 3.24 ± 2.79% (R2 = 0.9499) as compared to 4.77 ± 3.96% (R2 = 0.9213) using direct approaches. For general purpose SPECT, the averaged NMSE of the predicted AC images using the direct approaches was 2.57 ± 1.06% as compared to 1.37 ± 1.16% using the indirect approaches. CONCLUSIONS: We developed strategies of generating µ-maps for dedicated cardiac SPECT with small FOV. For both general purpose and dedicated SPECT, indirect approaches showed superior performance of AC than direct approaches.

Effect of Gd3+ , Bi3+ , or Sm3+ on luminescent properties of La2-x MgTiO6 :xEu3+ phosphors.

Single phase of Bi3+ , Gd3+ , Sm3+ and Eu3+ co-doped La2 MgTiO6 red phosphors were synthesized by high temperature solid-state method. The phase composition, morphology and fluorescent properties of the phosphors were analyzed by X-ray diffraction (XRD), scanning electron microscopy (SEM) and fluorescence spectrometer. The La2-x MgTiO6 :xEu3+ phosphors can be excited by UV (396 nm) and blue (465 nm) light-emitting diode (LED) chips and show a strong red emitting with dominated wavelength at 615 nm. The optimum doping concentration of Eu3+ ion for La2 MgTiO6 is x = 0.5. The luminescent intensities of 5 D0  â†’ 7 F2 transition of Eu3+ in La1.5-y MgTiO6 :0.5Eu3+ , yBi3+ /Gd3+ /Sm3+ were 1.31 times, 1.32 times and 1.88 times that of La1.5 MgTiO6 :0.5Eu3+ at y = 0.08, 0.06, 0.06 for Bi3+ , Gd3+ , or Sm3+ sensitizer, respectively. The chromaticity coordinates of La1.44 MgTiO6 :0.5Eu3+ , 0.06Sm3+ , (0.6342, 0.3513) were very close to those of the National Television Standard Committee (NTSC) standard red light coordinates.

Sol-gel preparation and luminescent properties of red-emitting phosphor Sr-Ba-Mo-W-O-(Eu(3+),Sm(3+)).

Two series of red-emitting phosphors Sr-Ba-Mo-W-O:Eu,Sm and Sr-Ba-Mo-W-O:Eu have been synthesized by a sol-gel method. The effects of the chemical composition, concentrations of Sm(3+) and Eu(3+), the Sr(2+)/Ba(2+) ratio, and the W(6+)/Mo(6+) ratio on the luminescent properties were investigated. The as-prepared phosphors were characterized by X-ray diffraction and Raman spectra. Results showed that single phases of the two series were prepared. The compositions of Sr0.6 Ba0.13Mo0.8 W0.2O4:Eu0.10Sm0.08 and Sr0.75Ba0.1Mo0.8 W0.2O4:Eu0.10 had the strongest luminescent intensity. The excitation spectra of Sm(3+), Eu(3+) co-doped phosphors were broader and the strongest peak moved to 404 nm when compared with that of Eu(3+) single-doped phosphors. The luminescent intensity of the Sr0.6Ba0.13Mo0.8W0.2O4:Eu0.10 Sm0.08 at 618 nm were 2.8 times greater than that of Sr0.75Ba0.1Mo0.8 W0.2O4:Eu0.10. The luminescent intensity of Sr0.6Ba0.13Mo0.8 W0.2 O4:Eu0.10Sm0.08 and Sr0.75Ba0.1Mo0.8W0.2O4:Eu0.10 at 150 °C decreased to 56.8% and 50.3% of the initial value at room temperature, respectively.

Luminescent properties of sol-gel processed red-emitting phosphor Ca0.6 Sr0.4-1.5x-0.5y Mo0.4 W0.6 O4:Eux Liy.

A series of red-emitting phosphors Ca0.6Sr(0.4-1.5x-0.5y)Mo0.4W0.6O4:Eux Liy (x = 0.02-0.12, y = 0-0.12) has been synthesized by a sol-gel method. The effects of calcining temperature, concentrations of Li(+) and Eu(3+) , and compensation ions on the luminescent properties were investigated. X-ray diffraction and scanning electron microscopic results showed that as-prepared phosphors were of single phase with several microns. The Li(+) compensated compositions showed remarkably intense red emission at 619 nm. The emission intensity of the series reached maximum for compositions at x = 0.08 and y = 0.08 when the calcining temperature was 900 °C.

Influence of Ce substitution for Bi in BiVO4 and the impact on the phase evolution and microwave dielectric properties.

In the present work, the (Bi1-xCex)VO4 (x ≤ 0.6) ceramics were prepared via a solid-state reaction method and all the ceramic samples could be densified below 900 °C. From the X-ray diffraction analysis, it is found that a monoclinic scheelite solid solution can be formed in the range x ≤ 0.10. In the range 0.20 ≤ x ≤ 0.60, a composite region with both monoclinic scheelite and tetragonal zircon solid solutions was formed and the content of the zircon phase increased with the calcined or sintering temperature. The refined lattice parameters of (Bi0.9Ce0.1)VO4 are a = 5.1801(0) Å, b = 5.0992(1) Å, c = 11.6997(8) Å, and γ = 90.346(0)° with the space group I112/b(15). The VO4 tetrahedron contracts with the substitution of Ce for Bi at the A site, and this helps to keep the specific tetrahedron chain stable in the monoclinic structure. The microwave dielectric permittivity was found to decrease linearly from 68 to about 26.6; meanwhile, the quality factor (Qf) value increased from 8000 GHz to around 23900 GHz as the x value increased from 0 to 0.60. The best microwave dielectric properties were obtained in a (Bi0.75Ce0.25)VO4 ceramic with a permittivity of ∼47.9, a Qf value of ∼18000 GHz, and a near-zero temperature coefficient of ∼+15 ppm/°C at a resonant frequency of around 7.6 GHz at room temperature. Infrared spectral analysis supported that the dielectric contribution for this system at microwave region could be attributed to the absorptions of structural phonon oscillations. This work presents a novel method to modify the temperature coefficient of BiVO4-type materials. This system of microwave dielectric ceramic might be an interesting candidate for microwave dielectric resonator and low-temperature cofired ceramic technology applications.

Structure, phase evolution, and microwave dielectric properties of (Ag0.5Bi0.5)(Mo0.5W0.5)O4 ceramic with ultralow sintering temperature.

In the present work, the microwave dielectric ceramic (Ag0.5Bi0.5)(Mo0.5W0.5)O4 was prepared by using the solid-state reaction method. (Ag0.5Bi0.5)(Mo0.5W0.5)O4 was found to crystallize in the scheelite structure, in which Ag(+) and Bi(3+) occupy the A site randomly with 8-coordination while Mo(6+) and W(6+) occupy the B site with 4-coordination, at a sintering temperature above 500 °C, with lattice parameters a = b = 5.29469(2) Å and c = 11.62114(0) Å, space group I4(1)/a (No. 88), and acceptable Rp = 9.38, Rwp = 11.2, and Rexp = 5.86. High-performance microwave dielectric properties, with permittivity ∼26.3, Qf value ∼10,000 GHz, and temperature coefficient ∼+20 ppm/°C, were obtained in the sample sintered at 580 °C. Its chemical compatibility with aluminum at its sintering temperature was revealed and confirmed by both X-ray and energy dispersive spectrometer analysis. This ceramic could be a good candidate for ultralow-temperature cofired ceramics.

Promotion of SO2 resistance of Ce-La/TiO2 denitrification catalysts by V doping.

Conventional cerium-based denitrification catalysts show good catalytic activity at moderate and high temperatures, but their denitrification performance may be decreased due to poisoning by SO2 in the flue gas. In this paper, V was introduced into Ce-La/TiO2 catalysts by a ball-milling method, and the effects of the V content on catalyst denitrification performance and SO2 resistance were investigated. Fourier-transform diffuse reflectance in situ infrared spectroscopy was used to examine the denitrification mechanism and evaluate the catalysts for surface acidity, redox characteristics, and SO2 adsorption. After introducing V, Brønsted acids played the dominant role in the catalytic reaction by increasing the number of acidic sites on the catalyst surface, adsorbing NH3 to participate in the reaction, and improving the sulfur resistance by inhibiting SO2 poisoning. The Ce3+ and O ratio on the catalyst surface were also enhanced by V doping, which reduced interactions between SO2 and the primary metal oxide active ingredients. The modified catalyst inhibited the formation of sulfate species on the catalyst surface and prevented the generation of additional nitrate species on the surface, which protected the main active sites. After V doping, the NH3-SCR reaction on the catalyst surface followed the Langmuir-Hinshelwood mechanism.

Changing Cinnamaldehyde Skeleton Achieves Antibacterial Nanoswitch.

Changeable substituent groups of organic molecules can provide an opportunity to clarify the antibacterial mechanism of organic molecules by tuning the electron cloud density of their skeleton. However, understanding the antibacterial mechanism of organic molecules is challenging. Herein, we reported a molecular view strategy for clarifying the antibacterial switch mechanism by tuning electron cloud density of cinnamaldehyde molecule skeleton. The cinnamaldehyde and its derivatives were self-assembled into nanosheets with excellent water solubility, respectively. The experimental results show that α-bromocinnamaldehyde (BCA) nanosheets exhibits unprecedented antibacterial activity, but there is no antibacterial activity for α-methylcinnamaldehyde nanosheets. Therefore, the BCA nanosheets and α-methylcinnamaldehyde nanosheets achieve an antibacterial switch. Theoretical calculations further confirmed that the electron-withdrawing substituent of the bromine atom leads to a lower electron cloud density of the aldehyde group than that of the electron-donor substituent of the methyl group at the α-position of the cinnamaldehyde skeleton, which is a key point in elucidating the antimicrobial switch mechanism. The excellent biocompatibility of BCA nanosheets was confirmed by CCK-8. The mouse wound infection model, H&E staining, and the crawling ability of drosophila larvae show that as-prepared BCA nanosheets are safe and promising for wound healing. This study provides a new strategy for the synthesis of low-cost organic nanomaterials with good biocompatibility. It is expected to expand the application of natural organic small molecule materials in antimicrobial agents.

Unified Noise-aware Network for Low-count PET Denoising with Varying Count Levels.

As PET imaging is accompanied by substantial radiation exposure and cancer risk, reducing radiation dose in PET scans is an important topic. However, low-count PET scans often suffer from high image noise, which can negatively impact image quality and diagnostic performance. Recent advances in deep learning have shown great potential for recovering underlying signal from noisy counterparts. However, neural networks trained on a specific noise level cannot be easily generalized to other noise levels due to different noise amplitude and variances. To obtain optimal denoised results, we may need to train multiple networks using data with different noise levels. But this approach may be infeasible in reality due to limited data availability. Denoising dynamic PET images presents additional challenge due to tracer decay and continuously changing noise levels across dynamic frames. To address these issues, we propose a Unified Noise-aware Network (UNN) that combines multiple sub-networks with varying denoising power to generate optimal denoised results regardless of the input noise levels. Evaluated using large-scale data from two medical centers with different vendors, presented results showed that the UNN can consistently produce promising denoised results regardless of input noise levels, and demonstrate superior performance over networks trained on single noise level data, especially for extremely low-count data.

Tether-entangled conjugated helices.

A new design concept, tether-entangled conjugated helices (TECHs), is introduced for helical polyaromatic molecules. TECHs consist of a linear polyaromatic ladder backbone and periodically entangling tethers with the same planar chirality. By limiting the length of tether, all tethers synchronously bend and twist the backbone with the same manner, and change it into a helical ribbon with a determinate helical chirality. The 3D helical features are customizable via modular synthesis by using two types of synthons, the planar chiral tethering unit (C 2 symmetry) and the docking unit (C 2h symmetry), and no post chiral resolution is needed. Moreover, TECHs possess persistent chiral properties due to the covalent locking of helical configuration by tethers. Concave-type and convex-type oligomeric TECHs are prepared as a proof-of-concept. Unconventional double-helix π-dimers are observed in the single crystals of concave-type TECHs. Theoretical studies indicate the smaller binding energies in double-helix π-dimers than conventional planar π-dimers. A concentration-depend emission is found for concave-type TECHs, probably due to the formation of double-helix π-dimers in the excited state. All TECHs show strong circularly polarized luminescence (CPL) with dissymmetric factors (|g lum|) generally over 10-3. Among them, the (P)-T4-tBu shows the highest |g lum| of 1.0 × 10-2 and a high CPL brightness of 316 M-1 cm-1.

Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation.

Image-to-image translation is a vital component in medical imaging processing, with many uses in a wide range of imaging modalities and clinical scenarios. Previous methods include Generative Adversarial Networks (GANs) and Diffusion Models (DMs), which offer realism but suffer from instability and lack uncertainty estimation. Even though both GAN and DM methods have individually exhibited their capability in medical image translation tasks, the potential of combining a GAN and DM to further improve translation performance and to enable uncertainty estimation remains largely unexplored. In this work, we address these challenges by proposing a Cascade Multi-path Shortcut Diffusion Model (CMDM) for high-quality medical image translation and uncertainty estimation. To reduce the required number of iterations and ensure robust performance, our method first obtains a conditional GAN-generated prior image that will be used for the efficient reverse translation with a DM in the subsequent step. Additionally, a multi-path shortcut diffusion strategy is employed to refine translation results and estimate uncertainty. A cascaded pipeline further enhances translation quality, incorporating residual averaging between cascades. We collected three different medical image datasets with two sub-tasks for each dataset to test the generalizability of our approach. Our experimental results found that CMDM can produce high-quality translations comparable to state-of-the-art methods while providing reasonable uncertainty estimations that correlate well with the translation error.

DuDoCFNet: Dual-Domain Coarse-to-Fine Progressive Network for Simultaneous Denoising, Limited-View Reconstruction, and Attenuation Correction of Cardiac SPECT.

Single-Photon Emission Computed Tomography (SPECT) is widely applied for the diagnosis of coronary artery diseases. Low-dose (LD) SPECT aims to minimize radiation exposure but leads to increased image noise. Limited-view (LV) SPECT, such as the latest GE MyoSPECT ES system, enables accelerated scanning and reduces hardware expenses but degrades reconstruction accuracy. Additionally, Computed Tomography (CT) is commonly used to derive attenuation maps ( µ -maps) for attenuation correction (AC) of cardiac SPECT, but it will introduce additional radiation exposure and SPECT-CT misalignments. Although various methods have been developed to solely focus on LD denoising, LV reconstruction, or CT-free AC in SPECT, the solution for simultaneously addressing these tasks remains challenging and under-explored. Furthermore, it is essential to explore the potential of fusing cross-domain and cross-modality information across these interrelated tasks to further enhance the accuracy of each task. Thus, we propose a Dual-Domain Coarse-to-Fine Progressive Network (DuDoCFNet), a multi-task learning method for simultaneous LD denoising, LV reconstruction, and CT-free µ -map generation of cardiac SPECT. Paired dual-domain networks in DuDoCFNet are cascaded using a multi-layer fusion mechanism for cross-domain and cross-modality feature fusion. Two-stage progressive learning strategies are applied in both projection and image domains to achieve coarse-to-fine estimations of SPECT projections and CT-derived µ -maps. Our experiments demonstrate DuDoCFNet's superior accuracy in estimating projections, generating µ -maps, and AC reconstructions compared to existing single- or multi-task learning methods, under various iterations and LD levels. The source code of this work is available at https://github.com/XiongchaoChen/DuDoCFNet-MultiTask.

Population-based deep image prior for dynamic PET denoising: A data-driven approach to improve parametric quantification.

The high noise level of dynamic Positron Emission Tomography (PET) images degrades the quality of parametric images. In this study, we aim to improve the quality and quantitative accuracy of Ki images by utilizing deep learning techniques to reduce the noise in dynamic PET images. We propose a novel denoising technique, Population-based Deep Image Prior (PDIP), which integrates population-based prior information into the optimization process of Deep Image Prior (DIP). Specifically, the population-based prior image is generated from a supervised denoising model that is trained on a prompts-matched static PET dataset comprising 100 clinical studies. The 3D U-Net architecture is employed for both the supervised model and the following DIP optimization process. We evaluated the efficacy of PDIP for noise reduction in 25%-count and 100%-count dynamic PET images from 23 patients by comparing with two other baseline techniques: the Prompts-matched Supervised model (PS) and a conditional DIP (CDIP) model that employs the mean static PET image as the prior. Both the PS and CDIP models show effective noise reduction but result in smoothing and removal of small lesions. In addition, the utilization of a single static image as the prior in the CDIP model also introduces a similar tracer distribution to the denoised dynamic frames, leading to lower Ki in general as well as incorrect Ki in the descending aorta. By contrast, as the proposed PDIP model utilizes intrinsic image features from the dynamic dataset and a large clinical static dataset, it not only achieves comparable noise reduction as the supervised and CDIP models but also improves lesion Ki predictions.

TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction.

Inter-frame motion in dynamic cardiac positron emission tomography (PET) using rubidium-82 (82Rb) myocardial perfusion imaging impacts myocardial blood flow (MBF) quantification and the diagnosis accuracy of coronary artery diseases. However, the high cross-frame distribution variation due to rapid tracer kinetics poses a considerable challenge for inter-frame motion correction, especially for early frames where intensity-based image registration techniques often fail. To address this issue, we propose a novel method called Temporally and Anatomically Informed Generative Adversarial Network (TAI-GAN) that utilizes an all-to-one mapping to convert early frames into those with tracer distribution similar to the last reference frame. The TAI-GAN consists of a feature-wise linear modulation layer that encodes channel-wise parameters generated from temporal information and rough cardiac segmentation masks with local shifts that serve as anatomical information. Our proposed method was evaluated on a clinical 82Rb PET dataset, and the results show that our TAI-GAN can produce converted early frames with high image quality, comparable to the real reference frames. After TAI-GAN conversion, the motion estimation accuracy and subsequent myocardial blood flow (MBF) quantification with both conventional and deep learning-based motion correction methods were improved compared to using the original frames. The code is available at https://github.com/gxq1998/TAI-GAN.