Imaging Applications Research Articles

Deep learning enhanced quantum holography with undetected photons

Holography is an essential technique of generating three-dimensional images. Recently, quantum holography with undetected photons (QHUP) has emerged as a groundbreaking method capable of capturing complex amplitude images. Despite its potential, the practical application of QHUP has been limited by susceptibility to phase disturbances, low interference visibility, and limited spatial resolution. Deep learning, recognized for its ability in processing complex data, holds significant promise in addressing these challenges. In this report, we present an ample advancement in QHUP achieved by harnessing the power of deep learning to extract images from single-shot holograms, resulting in vastly reduced noise and distortion, alongside a notable enhancement in spatial resolution. The proposed and demonstrated deep learning QHUP (DL-QHUP) methodology offers a transformative solution by delivering high-speed imaging, improved spatial resolution, and superior noise resilience, making it suitable for diverse applications across an array of research fields stretching from biomedical imaging to remote sensing. DL-QHUP signifies a crucial leap forward in the realm of holography, demonstrating its immense potential to revolutionize imaging capabilities and pave the way for advancements in various scientific disciplines. The integration of DL-QHUP promises to unlock new possibilities in imaging applications, transcending existing limitations and offering unparalleled performance in challenging environments.

Intelligent imaging technology applications in multidisciplinary hospitals: A systematic review.

With the rapid development of artificial intelligence technology, its applications in medical imaging have become increasingly extensive. This review aimed to analyze the current development status and future direction of intelligent imaging technology by investigating its application in various medical departments. To achieve this, we conducted a comprehensive search of various data sources up to 2024, including PubMed, Web of Science, and Google Scholar, based on the principle of comprehensive search. A total of 332 articles were screened, and after applying the inclusion and exclusion criteria, 56 articles were selected for this study. According to the findings, intelligent imaging technology exhibits robust image recognition capabilities, making it applicable across diverse medical imaging modalities within hospital departments. This technology offers an efficient solution for the analysis of various medical images by extracting and accurately identifying complex features. Consequently, it significantly aids in the detection and diagnosis of clinical diseases. Its high accuracy, sensitivity, and specificity render it an indispensable tool in clinical diagnostics and related tasks, thereby enhancing the overall quality of healthcare services. The application of intelligent imaging technology in healthcare significantly enhances the efficiency of clinical diagnostics, resulting in more accurate and timely patient assessments. This advanced technology offers a faster and more precise diagnostic approach, ultimately improving patient care and outcomes. This review analyzed the socioeconomic changes brought about by intelligent imaging technology to provide a more comprehensive evaluation. Also, we systematically analyzed the current shortcomings of intelligent imaging technology and its future development directions, to enable future research.

Indocyanine Blue (ICB) as a Functional Alternative to Indocyanine Green (ICG) for Enhanced 700 nm NIR Imaging

Despite significant advancements in bioimaging technology, only a limited number of fluorophores are currently approved for clinical applications. Indocyanine green (ICG) is the first FDA-approved near-infrared (NIR) fluorophore and has significantly advanced clinical interventions over the past three decades. However, its single-channel imaging at 800 nm emission is often insufficient for capturing comprehensive diagnostic information during surgery. In this study, we evaluate indocyanine blue (ICB), an ICG analog with a shorter polymethine bridge, as a promising candidate for multi-channel NIR imaging. ICB demonstrated peak absorption and emission approximately 100 nm shorter than ICG in aqueous solutions, placing it within the 700 nm range of the NIR window. Furthermore, ICB exhibited favorable solubility and optical properties in aqueous environments, supporting its potential for in vivo imaging applications. Notably, ICB shows rapid systemic clearance, likely due to its lower molecular weight, which facilitates clear visualization in angiography, cholangiography, and lymph node mapping with minimal background interference. Additionally, dual-channel imaging of tumors and lymph nodes was achieved using a tumor-targeting fluorophore in conjunction with ICB, illustrating the potential for enhanced intraoperative guidance. ICB emitting at 700 nm, therefore, can be useful in NIR imaging, broadening the possibilities for improved diagnostic accuracy and therapeutic outcomes in clinical settings.

Computationally efficient collimator-detector response compensation in high energy SPECT using 1D convolutions and rotations.

Modeling of the collimator-detector response (CDR) in SPECT reconstruction enables improved resolution and accuracy, and is thus important for quantitative imaging applications such as dosimetry. The implementation of CDR modeling, however, can become a computational bottleneck when there are substantial components of septal penetration and scatter in the acquired data, since a direct convolution-based approach requires large 2D kernels. This work proposes a 1D convolution and rotation-based CDR model that reduces reconstruction times but maintains consistency with models that employ 2D convolutions. To enable open-source development and use of these models in image reconstruction, we release a SPECTPSFToolbox repository for the PyTomography project on GitHub. A 1D/rotation-based CDR model was formulated and subsequently fit to Monte Carlo point source data representative of Lu-177, I-131, and Ac-225 imaging. Computation times of (i) the proposed 1D/rotation-based model and (ii) a traditional model that uses 2D convolutions were compared for typical SPECT matrix sizes. Both CDR models were then used in the reconstruction of Monte Carlo, physical phantom, and patient data; the models were compared by quantifying total counts in hot regions of interest (ROIs) and activity contrast between hot ROIs and background regions. For typical matrix sizes in SPECT reconstruction, application of the 1D/rotation-based model provides a two-fold computational speed-up over the 2D model when running on GPU. Only small differences between the 1D/rotation-based and 2D models (order of 1%) were obtained for count and contrast quantification in select ROIs. A technique for CDR modeling in SPECT was proposed that (i) significantly speeds up reconstruction times, and (ii) yields nearly identical reconstructions to traditional 2D convolution based CDR techniques. The released toolbox will permit open-source development of similar models for different isotopes and collimators.

Multiphoton Excited Fluorescence Imaging over Metal-Organic Frameworks.

Multiphoton excited fluorescence (MPEF) imaging has emerged as a powerful tool for visualizing biological processes with high spatial and temporal resolution. Metal-organic frameworks (MOFs), a class of porous materials composed of metal ions or clusters coordinated with organic ligands, have recently gained attention for their unique optical properties and potential applications in MPEF imaging. This review provides a comprehensive overview of the design, synthesis, and applications of multiphoton excited fluorescence imaging using MOFs. We discuss the principles behind the fluorescence behavior of MOFs, explore strategies to enhance their photophysical properties, and showcase their applications in bioimaging. Additionally, we address the current challenges and future prospects in this rapidly evolving field, highlighting the potential of multiphoton excited fluorescence imaging by MOFs for advancing our understanding of complex biological processes.

Realisation of an Application Specific Multispectral Snapshot-Imaging System Based on Multi-Aperture-Technology and Multispectral Machine Learning Loops

Multispectral imaging (MSI) enables the acquisition of spatial and spectral image-based information in one process. Spectral scene information can be used to determine the characteristics of materials based on reflection or absorption and thus their material compositions. This work focuses on so-called multi aperture imaging, which enables a simultaneous capture (snapshot) of spectrally selective and spatially resolved scene information. There are some limiting factors for the spectral resolution when implementing this imaging principle, e.g., usable sensor resolutions and area, and required spatial scene resolution or optical complexity. Careful analysis is therefore needed for the specification of the multispectral system properties and its realisation. In this work we present a systematic approach for the application-related implementation of this kind of MSI. We focus on spectral system modeling, data analysis, and machine learning to build a universally usable multispectral loop to find the best sensor configuration. The approach presented is demonstrated and tested on the classification of waste, a typical application for multispectral imaging.

Engineered Strategies for Lipid Droplets-Targeted AIEgens Based on Tetraphenylethene

Lipid droplets (LDs), once regarded as inert fat particles, have been ignored by scientific researchers for a long time. Now, studies have shown that LDs are dynamic organelles used to store neutral lipids in cells and maintain cell stability. The abnormality of intracellular LDs usually causes metabolic disorders in the body, such as obesity, atherosclerosis, diabetes, and cancer, so the LDs have attracted wide attention. The traditional small molecules used for LDs recognition seriously affect the imaging effect due to their poor photo-stability, low signal-to-noise ratios, and aggregation-induced quenching (ACQ). In contrast to ACQ, aggregation-induced emission (AIE) materials, with structural modifiability, can make up for the aforementioned deficiencies in the field of fluorescence imaging and have attracted much attention. In this review, the importance of LDs in vivo, the design principles for LDs recognition, and the recent research progress of AIE compounds with tetraphenylethene (TPE) structure in LDs targets are reviewed. We expect this review to further provide researchers with feasible methods and protocols for expanding LDs identification, imaging, and other applications.

Investigations on the Performance of a 5 mm CdTe Timepix3 Detector for Compton Imaging Applications

Nuclear power plant decommissioning requires the rapid and accurate classification of radioactive waste in narrow spaces and under time constraints. Photon-counting detector technology offers an effective solution for the quick classification and detection of radioactive hotspots in a decommissioning environment. This paper characterizes a 5 mm CdTe Timepix3 detector and evaluates its feasibility as a single-layer Compton camera. The sensor’s electron mobility–lifetime product and resistivity are studied across bias voltages ranging from −100 V to −3000 V, obtaining values of μeτe = (1.2 ± 0.1) × 10−3 cm2V−1, and two linear regions with resistivities of ρI=(5.8±0.2) GΩ cm and ρII=(4.1±0.1) GΩ cm. Additionally, two calibration methodologies are assessed to determine the most suitable for Compton applications, achieving an energy resolution of 16.3 keV for the 137Cs photopeak. The electron’s drift time in the sensor is estimated to be (122.3 ± 7.4) ns using cosmic muons. Finally, a Compton reconstruction of two simultaneous point-like sources is performed, demonstrating the detector’s capability to accurately locate radiation hotspots with a ∼51 cm resolution.

Amphiphilic self-assembling peptides: formulation and elucidation of functional nanostructures for imaging and smart drug delivery.

The rational design of self-assembled peptide-based nanostructures for theranostics applications requires in-depth physicochemical characterization of the peptide nanostructures, to understand the mechanism and the interactions involved in the self-assembly, allowing a better control of the objects' physicochemical and functional properties for theranostic applications. In this work, several complementary characterization methods, such as dynamic light scattering, transmission electron microscopy, circular dichroism, Taylor dispersion analysis, and capillary electrophoresis, were used to study and optimize the self-assembly of pH-sensitive short synthetic amphiphilic peptides containing an RGD motif for active targeting of tumor cells and smart drug delivery. The combined methods evidenced the spontaneous formation of nanorods (L = 50nm, d = 10nm) at pH 11, stabilized by β-sheets. To complement with imaging properties for diagnosis, a new strategy was developed by designing an optimized peptide sequence to allow for efficient functionalization with a contrast agent, while preserving the self-assembling properties. Co-assemblies of the peptide and its derivatives, after peptide modification with a gadolinium complex, exhibited similar nanorod structures and required properties for drug delivery and imaging applications in vivo.

Late-Stage Rapid [18F]Trifluoromethyl Radiolabeling of Terminal Alkenes at Room Temperature.

We report an efficient, metal-free method for late-stage rapid [18F]trifluoromethyl radiolabeling of terminal alkenes at room temperature. Utilizing 3,3-difluoroallyl sulfonium salts as precursors, the process achieves high radiochemical yields (up to 94 ± 2%) in just 30 s, with excellent functional group tolerance. This method offers a simplified and efficient pathway to produce [18F]trifluoromethylated terminal alkene compounds, enabling their application in PET imaging and expanding the chemical space for drug discovery.

MRNA-encoded fluorescent proteins enable superior organelle labeling for live cell imaging.

Live cell labeling of various organelles is of great demand in the research field of cell biology. However, current approaches often lack an optimal balance between efficiency and versatility. We took advantage of chemical modified mRNA to express various organelle located fluorescent proteins. This approach facilitated highly efficient multi-organelle labeling across diverse cell types, both invitro and invivo. The application of mRNA-based organelle markers offers faster and more efficient transfection and expression compared to plasmids. When expressing fluorescent proteins in neuronal cells, it is faster and safer compared to viral vectors. Notably, this approach excels in rapidly labeling organelles, making it highly effective for dynamic live cell imaging applications. By leveraging this tool, we unveiled the unique behaviors of mitochondria and the endoplasmic reticulum during spike protein-mediated cell fusion, a critical event in SARS-CoV-2 viral entry. Thus, our results demonstrate the potency of mRNA-encoded fluorescent proteins as powerful tools for advancing biological research.

Cutting Edge Microscopic Intraoperative Tissue Assessment for Guidance in Oncologic Surgery: A Systematic Review of the Role of Optical Coherence Tomography.

There is a demand for intraoperative diagnostic support and image guidance in oncological surgery. Novel techniques can provide images similar to histopathological slides within a few minutes. Optical coherence tomography (OCT) and full-field OCT (FF-OCT) provide images with resolution greater than a hundred micrometers without the need for exogenous contrast agents or specimen staining. The aim of this systematic review was to assess the current clinical applications of OCT and dynamic cell imaging (DCI) in oncologic surgery, examining the translation challenges and proposing perspectives for improving future clinical applications. The study adhered to the PRISMA guidelines. PubMed, Google Scholar, and ClinicalTrials.gov were searched up to July 2024. Manuscripts reporting data on OCT and (D)-FF-OCT application in oncologic surgery were included in the qualitative analysis. Thirty-one studies met the inclusion criteria. Most were from the fields of dermatologic (25.8%) and breast cancer (29%) surgery, followed by prostate and bladder (9.6%), ovarian (9.6%), head and neck (6.4%), gastrointestinal (6.4%), hepato-biliary (3.2%), and general surgery (9.6%). The majority of articles focused on FF-OCT and DCI (80.6%). Compared with the gold standard of final pathology, the OCT sensitivity ranged between 66.7 and 94%, the specificity between 64 and 100%, and the accuracy between 73 and 96%. The medical use of OCT has expanded from ophtalmology to other fields including gastroenterology and oncology and, with techniques such as FF-OCT and DCI, can enable rapid intraoperative diagnosis beyond classic histopathology.

Steric and Distance Effect on Electron Transfer in Dibenzo-Fused BODIPY-Based Photoredox Catalysts.

π-Extended BODIPY compounds are a compelling class of fluorophores known for their red or near-infrared (NIR) emission and high quantum yields, which are crucial for applications in materials science, solar cells, and biomedical imaging. Our recent study shows that we can use a dibenzo-fused BODIPY as a singlet-driven red photoredox catalyst by installing a simple electron donor group. Despite their potential in these applications, knowledge of electron transfer reactions involving dibenzo-fused BODIPY is still scarce. This paper presents the synthesis and systematic photophysical investigations of donor-acceptor (D-A) and donor-bridge-acceptor (D-bridge-A) series of dibenzo-fused BODIPY with N,N'-diethylaniline fragments serving as an electron donor. We examined the effects of methyl substituents and bridge length on the rates of photoinduced electron transfer (PeT). Through steady-state and time-resolved optical spectroscopy, electrochemistry, and density functional theory calculations, we elucidated how these simple structural modifications controlled the PeT rates and examined their impacts on catalytic activities in atom transfer radical addition (ATRA) reactions. Our results support previous studies on the (D-A) design of red heavy atom-free photocatalysts.

High-Performance All-Inorganic Perovskite Tandem Photodetectors With Bi2TeO6 Layer Enabled by Enhanced Dual Pyro-Phototronic Effect for Triple-Encryption Imaging Sensing System with Programmable Logic Gate.

As the focus on information security continues to intensify, encrypted imaging sensing technology becomes increasingly indispensable. However, the widespread application of encrypted imaging sensing technology is hindered by high manufacturing costs and complex system construction. Herein, an all-inorganic perovskite/perovskite tandem self-powered photodetector (PDs) is reported, incorporated with Bi2TeO6 layer to enahnce dual pyro-phototronic effect, to realize an innovated encryption imaging sensing system with programmable logic gate. The PDs reach responsivity of 1.46 A W-1 and detectivity of 3.44 × 1013 Jones, the corresponding EQE reaches 342%, which is ≈75.48 times greater than that without pyro-phototronic effect. The outstanding performance resulting from dual pyro-phototronic effect in Cs2PbI2Cl2 perovskite and Bi2TeO6/CsSn0.5Pb0.5IBr2 interface, and optimizing band arrangement from the oxidized Bi2TeO6 layer. The photovoltaic and pyro-phototronic signal of PDs can still be clearly distinguished under 8 kHz pulsed laser. More importantly, the encryption imaging sensing system achieves simultaneous outputs of triple image information, and their programmable optoelectronic logic gate can executesix distinct logical functions, including "OR", "AND", "XOR", "NAND", "NOR" and "XNOR". This research not only provides a feasible strategy for realizing the outstanding pyro-phototronic effect of all-inorganic perovskite materials, but also presents novel insights for designingencrypted imaging sensing technology.

Ultra-wideband and high isolation using defected ground structure modified bowtie antenna array for through wall imaging applications

The design and analysis of an ultra-wideband with high isolation characteristics, utilizing a modified bowtie antenna and coplanar waveguide feeding technique is presented in this paper. Grooves are added to the ground plane's entire structure to reduce the capacitive coupling between the patch and the ground plane. The grooves in the ground plane enhance the impedance matching and radiation efficiency across the ultrawideband frequency range. Also, defected ground structures (DGS) are used to improve isolation between the two antennas. It is novel and different in that it uses defective ground structures (DGS) to provide high isolation (−<50dB) with a high gain of 6.5 dBi and a large impedance bandwidth (155%). Compared to other documented methods, the antenna's design step is very simple, the overall size is small, larger bandwidth (13.5 GHz) and achieves high isolation due to DGS.

Engineering Zn/Fe Mixed Metal Oxides with Tunable Structural and Magnetic Properties for Magnetic Particle Imaging.

Engineering magnetic nanoparticles with tunable structural properties and magnetism is critical to develop desirable magnetic particle imaging (MPI) tracers for biomedical applications. Here we present a new superparamagnetic metal oxide nanoparticle with a controllable chemical composition and magnetism for imaging tumor xenografts in living mice. Superparamagnetic Zn/Fe mixed metal oxide (ZnFe-MMO) nanoparticles are fabricated via a facile one-pot co-precipitation method in water followed by thermal decomposition with tunable Zn/Fe ratios and at various calcination temperatures. This work, for the first time, presented LDH-derived metal oxides for an MPI application. The metal composition is tunable to present an optimized MPI performance. The analytical results demonstrate that ZnFe-MMO nanoparticles at the designed molar ratio of Zn/Fe = 2:1 after 650 °C calcination demonstrate a higher saturation magnetization (MS) value and optimal MPI signal than the samples presented with other conditions. The excellent biocompatibility of ZnFe-MMO is demonstrated in both breast cancer cells and fibroblast cell cultures. In vivo imaging of 4T1 tumor xenografts in mice using ZnFe-MMO as a tracer showed that the mean signal intensity is 1.27-fold higher than the commercial tracer VivoTrax at 72 h post-injection, indicating ZnFe-MMO's promise for prolonged MPI imaging applications.

The Effects of Manufacturing Errors on the Performance of Acoustic Metamaterial Lenses Operating in the MHz Regime

This article explores the use of acoustical metamaterials to design lenses in the megahertz frequency range of relevance to applications in nondestructive testing and medical imaging. In particular, the effect of manufacturing errors on their focusing performance is quantified. A rapid method for including manufacturing errors is described and this is used to perform Monte Carlo simulations of wave pressure fields from lenses with manufacturing errors. In this process, the required time delay distribution for a target focal length is calculated and the acoustical lenses with a chosen unit cell type are designed. Manufacturing errors of the unit cells are then added, considering their statistical properties and a large number of realizations. As an example, an acoustical lens with a focal length of 76 mm at a frequency of 1 MHz is designed using three different unit cell types: steel cross unit cell, resin circular void unit cell, and silicone–resin layered unit cell. Finally, the resulting acoustic pressure fields are computed using a Huygens’ principle model to assess the effects of manufacturing errors on lens performance, i.e., the focal length and the size of the focal spot. It is shown that the performance of lenses consisting of silicone–resin layered units is less affected by the manufacturing errors than for lenses constructed with the other unit cells. This study paves the way for selecting a suitable combination of metamaterial unit cell and manufacturing method to enable acceptable lens imaging performance.

Ultrahigh piezoelectric properties and high transparency relaxor ferroelectric single crystals obtained by the combination of rare-earth doping and AC-poling

High-performance relaxor ferroelectric single crystals, such as Pb(Mg1/3Nb2/3)O3–PbTiO3 (PMN–PT), play a crucial role in the applications of medical ultrasonic imaging due to their high piezoelectric properties. In this study, we successfully grew a 2-in. Eu-doped PMN–PT single crystal whose composition variation and electrical properties were systematically investigated. It was found that the PT content of the crystal boule increased gradually along the growth direction, while the change of Eu3+ content was opposite. The property results show that Eu-doped PMN–PT single crystals exhibit a remarkable piezoelectric coefficient of 3300 pC N−1 at DC-poling while maintaining the rhombohedral phase to a tetragonal phase transition temperature (TRT) at 88 °C and the coercive field (EC) at 2.7 kV cm−1, higher to the undoped single crystals. Through the study of the local structure of Eu-PMN–PT, it illustrated that the introduction of Eu3+ increased the standard deviation of an A sublattice from 3.0% to 4.8%. The dopant simultaneously enhanced a tetragonal phase ratio and local structural heterogeneity, resulting in improved piezoelectric properties and temperature stability of the crystal. We further treated the doped crystals with AC-poling to obtain ultrahigh piezoelectric performance (d33 &amp;gt; 4000 pC N−1) and high transparency. This work provides a new approach to achieve a relaxor ferroelectric single crystal with high performance and transparency with good temperature stability, which could be the material of choice for optoelectronic devices in the future.

Analysis of the Relationship Between Scale Invariant Feature Transform Keypoint Properties and Their Invariance to Geometrical Transformation Applied to Cone-Beam Computed Tomography Images

Image registration is a crucial post-processing technique in biomedical imaging, enabling the alignment and integration of images from various sources to facilitate accurate diagnosis, treatment planning, and longitudinal studies. This paper explores the application of Scale Invariant Feature Transform (SIFT), a robust feature-based method for the alignment of biomedical images. SIFT is particularly advantageous due to its invariance to scale, rotation, and affine transformations, making it well-suited for handling the diverse and complex nature of biomedical images. However, SIFT was not initially developed specifically for medical imaging applications, so it is necessary to adapt the algorithm to those kinds of images. In particular, this work was focused on images obtained with Cone-Beam Computed Tomography (CBCT) technology. Besides fine-tuning SIFT parameters on a case-by-case basis, the novelty of this work consists of finding the optimal SIFT parameters on the basis of the keypoints stability. A statistical analysis throughout a dataset of images obtained with CBCT technology was performed to find the best SIFT parameters setting, in terms of computational cost and result quality, compared to default presets.

Carbon Dots with Charge Storage Ability Promote the Red Emission of TFB via Carrier Secondary Injection.

Dual-emission light-emitting diodes (DEDs) have great promising applications in medical imaging, optical communication, data storage, and three-dimensional display. The precise material design and advanced packaging technology for the construction of DEDs are still key challenges for practical application. We demonstrate a straightforward strategy to construct DEDs that deviates from traditional approaches, utilizing commercially available luminescent material of poly(9,9-dioctylfluorene-co-N-(4-(3-methylpropyl))diphenylamine) (TFB) and carbon dots (CDs). In the DEDs, the mixture of CDs and TFB was used as the luminescent layer, which exhibits dual-wavelength emission located at 436 and 632 nm, respectively. Notably, the CDs, with charge storage ability, can store the interfacial charges, reinject the carriers into TFB, and then facilitate the long-wavelength (632 nm) emission from TFB. This work provides a new way for the design and construction of fresh DEDs through the CD-based interfacial charge transport process.