Single Acquisition Research Articles

A Gated TIMS FTICR MS Instrument to Decipher Isomeric Content of Complex Organic Mixtures.

Modern research faces increasingly complex materials with a constant need for new analytical strategies that can provide deeper levels of chemical insight. Ultrahigh resolution mass spectrometry (MS), particularly Fourier transform ion cyclotron resonance (FTICR) MS, has provided a robust analytical foundation. However, MS alone offers limited structural information. Here, we present the first implementation and results from an FTICR MS with fully integrated dual accumulation analysis with gated trapped ion mobility spectrometry (gTIMS) capability. The drastically extended charge capacity and parallel accumulation facilitate the analysis of complex mixtures. We achieved a high dynamic range of 4 orders of magnitude within a single FTICR acquisition event. Simultaneously, the valuable linear relationship between the TIMS elution voltage and reduced mobility was retained over a wide mobility range. Benchmarking the instrument performance with Suwannee River fulvic acid (SRFA) by variable ramp gTIMS analysis allowed separation and unambiguous assignment of different charge state distributions. Application to bio-oils has proven the capability to distinguish the isomeric diversity in these ultracomplex samples, while maintaining the expected FTICR MS resolving power and mass accuracy. Valuable information about the molecular distribution, isomeric diversity, and main molecular differences could directly be extracted within the analysis time of a classical "dilute and shoot" direct infusion experiment. The development of this fully integrated and flexible gTIMS with FTICR MS analysis possesses the potential to significantly change the current landscape of high-resolution mass spectrometric analysis of complex mixtures through the added insight of isomeric complexity afforded by TIMS. The exploration of the added IMS dimension promises transformative effects across diverse fields including energy transition, environmental studies, and biological research.

Collaborative robotics to enable ultra-high-throughput IR-MALDESI

Over the last 5 years, IR-MALDESI-MS (Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry) has been demonstrated for use in a range of high-throughput biochemical and cellular assays with remarkable sample acquisition rates up to 22 Hz for a single 384-well assay plate. With such high single plate acquisition rates, the rate limiting step becomes how fast subsequent plates can be presented to the MS for analysis. To make this transfer as fast as possible while maintaining safe operation in a laboratory environment, we developed a collaborative robotic plate transfer system (CRPTS) that combines a 6-axis robot with dual plate grippers, a 7th axis conveyor stage, and a 420-plate capacity sample loading window. As a demonstration of the throughput and flexibility of CRPTS, we performed a biochemical assay that monitored the oxidation of tris(2-carboxyethyl)phosphine (TCEP) to screen for nuisance compounds. Using continuous and step motion scan profiles, we analyzed 158,799 compounds contained in 448 assay plates over the course of 12.5 h (Z-Factor=0.87) and 17.5 h (Z-factor=0.99), respectively. Extrapolating these results enables the screening of a million compounds within 6–7 working days.

Single ion mobility monitoring (SIM2) stitching method for high-throughput and high ion mobility resolution chiral analysis

Chiral analysis is of high interest in many fields such as chemistry, pharmaceuticals and metabolomics. Mass spectrometry and ion mobility spectrometry are useful analytical tools, although they cannot be used as stand-alone methods. Here, we propose an efficient strategy for the enantiomer characterization of amino acids (AAs) using non-covalent copper complexes. A single ion mobility monitoring (SIM2) method was applied on a TIMS-ToF mass spectrometer to maximize the detection and mobility separation of isomers. Almost all of the 19 pairs of proteinogenic AA enantiomers could be separated with at least one combination with the chiral references L-Phe and L-Pro. Furthermore, we extended the targeted SIM2 method by stitching several mobility ranges, in order to be able to analyze complex mixtures in a single acquisition while maintaining high mobility resolution. Most of the enantiomeric pairs of AAs separated with the SIM2 method were also detected with this approach. The SIM2 stitching method thus opens the way to a more comprehensive chiral analysis with TIMS-ToF instruments.Graphical

Integration of large and diverse angiosperm DNA fragments into Asian Gnetum mitogenomes

BackgroundHorizontal gene transfer (HGT) events have rarely been reported in gymnosperms. Gnetum is a gymnosperm genus comprising 25‒35 species sympatric with angiosperms in West African, South American, and Southeast Asian rainforests. Only a single acquisition of an angiosperm mitochondrial intron has been documented to date in Asian Gnetum mitogenomes. We wanted to develop a more comprehensive understanding of frequency and fragment length distribution of such events as well as their evolutionary history in this genus.ResultsWe sequenced and assembled mitogenomes from five Asian Gnetum species. These genomes vary remarkably in size and foreign DNA content. We identified 15 mitochondrion-derived and five plastid-derived (MTPT) foreign genes. Our phylogenetic analyses strongly indicate that these foreign genes were transferred from diverse eudicots—mostly from the Rubiaceae genus Coptosapelta and ten genera of Malpighiales. This indicates that Asian Gnetum has experienced multiple independent HGT events. Patterns of sequence evolution strongly suggest DNA-mediated transfer between mitochondria as the primary mechanism giving rise to these HGT events. Most Asian Gnetum species are lianas and often entwined with sympatric angiosperms. We therefore propose that close apposition of Gnetum and angiosperm stems presents opportunities for interspecific cell-to-cell contact through friction and wounding, leading to HGT.ConclusionsOur study reveals that multiple HGT events have resulted in massive amounts of angiosperm mitochondrial DNA integrated into Asian Gnetum mitogenomes. Gnetum and its neighboring angiosperms are often entwined with each other, possibly accounting for frequent HGT between these two phylogenetically remote lineages.

Free-breathing, fat-corrected T1 mapping of the liver with stack-of-stars MRI, and joint estimation of T1, PDFF, , and .

Quantitative T1 mapping has the potential to replace biopsy for noninvasive diagnosis and quantitative staging of chronic liver disease. Conventional T1 mapping methods are confounded by fat and inhomogeneities, resulting in unreliable T1 estimations. Furthermore, these methods trade off spatial resolution and volumetric coverage for shorter acquisitions with only a few images obtained within a breath-hold. This work proposes a novel, volumetric (3D), free-breathing T1 mapping method to account for multiple confounding factors in a single acquisition. Free-breathing, confounder-corrected T1 mapping was achieved through the combination of non-Cartesian imaging, magnetization preparation, chemical shift encoding, and a variable flip angle acquisition. A subspace-constrained, locally low-rank image reconstruction algorithm was employed for image reconstruction. The accuracy of the proposed method was evaluated through numerical simulations and phantom experiments with a T1/proton density fat fraction phantom at 3.0 T. Further, the feasibility of the proposed method was investigated through contrast-enhanced imaging in healthy volunteers, also at 3.0 T. The method showed excellent agreement with reference measurements in phantoms across a wide range of T1 values (200 to 1000 ms, slope = 0.998 (95% confidence interval (CI) [0.963 to 1.035]), intercept = 27.1 ms (95% CI [0.4 54.6]), r2 = 0.996), and a high level of repeatability. In vivo imaging studies demonstrated moderate agreement (slope = 1.099 (95% CI [1.067 to 1.132]), intercept = -96.3 ms (95% CI [-82.1 to -110.5]), r2 = 0.981) compared to saturation recovery-based T1 maps. The proposed method produces whole-liver, confounder-corrected T1 maps through simultaneous estimation of T1, proton density fat fraction, and in a single, free-breathing acquisition and has excellent agreement with reference measurements in phantoms.

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging.

Pulmonary magnetic resonance imaging (MRI) offers a variety of radiation-free techniques tailored to assess regional lung ventilation or its surrogates. These techniques encompass direct measurements, exemplified by hyperpolarized gas MRI and fluorinated gas MRI, as well as indirect measurements facilitated by oxygen-enhanced MRI and proton-based Fourier decomposition (FD) MRI. In recent times, there has been substantial progress in the field of FD MRI, which involved improving spatial/temporal resolution, refining sequence design and postprocessing, and developing a comprehensive whole-lung approach. The two-dimensional (2D) phase-resolved functional lung (PREFUL) MRI stands out as an FD-based approach developed for the comprehensive assessment of regional ventilation and perfusion dynamics, all within a single MR acquisition. Recently, a new advancement has been made with the development of 3D PREFUL to assess dynamic ventilation of the entire lung using 8 min exam with a self-gated sequence. The 3D PREFUL acquisition involves employing a stack-of-stars spoiled-gradient-echo sequence with a golden angle increment. Following the compressed sensing image reconstruction of approximately 40 breathing phases, all the reconstructed respiratory-resolved images undergo registration onto a fixed breathing phase. Subsequently, the ventilation parameters are extracted from the registered images. In a study cohort comprising healthy volunteers and patients with chronic obstructive pulmonary disease, the 3D PREFUL ventilation parameters demonstrated strong correlations with measurements obtained from pulmonary function tests. Additionally, the interscan repeatability of the 3D PREFUL technique was deemed to be acceptable, indicating its reliability for repeated assessments of the same individuals. In summary, 3D PREFUL ventilation MRI provides a whole lung coverage and captures ventilation dynamics with enhanced spatial resolution compared to 2D PREFUL. 3D PREFUL technique offers a cost-effective alternative to hyperpolarized 129Xe MRI, making it an attractive option for patient-friendly evaluation of pulmonary ventilation.

Resting State Functional Networks in Gliomas: Validation With Direct Electric Stimulation of a New Tool for Planning Brain Resections.

Precise mapping of functional networks in patients with brain tumor is essential for tailoring personalized treatment strategies. Resting-state functional MRI (rs-fMRI) offers an alternative to task-based fMRI, capable of capturing multiple networks within a single acquisition, without necessitating task engagement. This study demonstrates a strong concordance between preoperative rs-fMRI maps and the gold standard intraoperative direct electric stimulation (DES) mapping during awake surgery. We conducted an analysis involving 28 patients with glioma who underwent awake surgery with DES mapping. A total of 100 DES recordings were collected to map sensorimotor (SMN), language (LANG), visual (VIS), and speech articulation cognitive domains. Preoperative rs-fMRI maps were generated using an updated version of the ReStNeuMap software, specifically designed for rs-fMRI data preprocessing and automatic detection of 7 resting-state networks (SMN, LANG, VIS, speech articulation, default mode, frontoparietal, and visuospatial). To evaluate the agreement between these networks and those mapped with invasive cortical mapping, we computed patient-specific distances between them and intraoperative DES recordings. Automatically detected preoperative functional networks exhibited excellent agreement with intraoperative DES recordings. When we spatially compared DES points with their corresponding networks, we found that SMN, VIS, and speech articulatory DES points fell within the corresponding network (median distance = 0 mm), whereas for LANG a median distance of 1.6 mm was reported. Our findings show the remarkable consistency between key functional networks mapped noninvasively using presurgical rs-fMRI and invasive cortical mapping. This evidence highlights the utility of rs-fMRI for personalized presurgical planning, particularly in scenarios where awake surgery with DES is not feasible to protect eloquent areas during tumor resection. We have made the updated tool for automated functional network estimation publicly available, facilitating broader utilization of rs-fMRI mapping in various clinical contexts, including presurgical planning, functional reorganization over follow-up periods, and informing future treatments such as radiotherapy.

Integrated Photoelectrochemical-SERS Platform Based on Plasmonic Metal-Semiconductor Heterostructures for Multidimensional Charge Transfer Analysis and Enhanced Patulin Detection.

Comprehending the charge transfer mechanism at the semiconductor interfaces is crucial for enhancing the electronic and optical performance of sensing devices. Yet, relying solely on single signal acquisition methods at the interface hinders a comprehensive understanding of the charge transfer under optical excitation. Herein, we present an integrated photoelectrochemical surface-enhanced Raman spectroscopy (PEC-SERS) platform based on quantum dots/metal-organic framework (CdTe/Yb-TCPP) nanocomposites for investigating the charge transfer mechanism under photoexcitation in multiple dimensions. This integrated platform allows simultaneous PEC and SERS measurements with a 532 nm laser. The obtained photocurrent and Raman spectra of the CdTe/Yb-TCPP nanocomposites are simultaneously influenced by variable bias voltages, and the correlation between them enables us to predict the charge transfer pathway. Moreover, we integrate gold nanorods (Au NRs) into the PEC-SERS system by using magnetic separation and DNA biometrics to construct a biosensor for patulin detection. This biosensor demonstrates the voltage-driven ON/OFF switching of PEC and SERS signals, a phenomenon attributed to the plasmon resonance effect of Au NRs at different voltages, thereby influencing charge transfer. The detection of patulin in apples verified the applicability of the biosensor. The study offers an efficient approach to understanding semiconductor-metal interfaces and presents a new avenue for designing high-performance biosensors.

Learning to learn: Single session acquisition of new rules by freely moving mice.

Learning from examples and adapting to new circumstances are fundamental attributes of human cognition. However, it is unclear what conditions allow for fast and successful learning, especially in nonhuman subjects. To determine how rapidly freely moving mice can learn a new discrimination criterion (DC), we design a two-alternative forced-choice visual discrimination paradigm in which the DCs governing the task can change between sessions. We find that experienced animals can learn a new DC after being exposed to only five training and three testing trials. The propensity for single session learning improves over time and is accurately predicted based on animal experience and criterion difficulty. After establishing the procedural learning of a paradigm, mice continuously improve their performance in new circumstances. Thus, mice learn to learn.

The use of pencil ionization chamber with temporal readout capabilities to measure CT beam full width half maximum.

Measurement of Computed Tomography (CT) beam width is required by accrediting and regulating bodies for routine physics evaluations due to its direct correlation to patient dose. Current methods for performing CT beam width measurement require special hardware, software, and/or consumable films. Today, most 100-mm pencil chambers with a digital interface used to evaluate Computed Tomography Dose Index (CTDIvol) have a sufficiently high sampling rate to reconstruct a high-resolution dose profile for any acquisition mode. The goal of this study is to measure the CT beam width from the sampled dose profile under a single helical acquisition with the 100-mm pencil chamber used for CTDIvol measurements. The dose profiles for different scanners were measured for helical scans with varying collimation settings using a 100-mm pencil chamber placed at the isocenter and co-moving with the patient table. The measured dose profiles from the 100-mm pencil chamber were corrected for table attenuation by extracting a periodic correction function (PCF) to eliminate table interference. The corrected dose profiles were then deconvolved with the response function of the chamber to compute the beam profile. The beam width was defined by the full width half maximum (FWHM) of the resulting beam profile. Reference dose profiles were also measured using Gafchromic film for comparison. The beam widths, estimated using the innovative deconvolution method from the 100-mm pencil chamber, exhibit an average percentage difference of 1.6±1.8 when compared with measurements obtained through Gafchromic film for beam width assessment. The proposed approach to deconvolve the pencil chamber response demonstrates the potential of obtaining the CT beam width at high accuracy without the need of special hardware, software, or consumable films. This technique can improve workflow for routine performance evaluation of CT systems.

Experimental measurement of local noise power spectrum (NPS) in photon counting detector-CT (PCD-CT) using a single data acquisition.

Accurate noise power spectra (NPS) measurement in clinical X-ray CT exams is challenging due to the need for repeated scans, which expose patients to high radiation risks. A reliable method for single CT acquisition NPS estimation is thus highly desirable. To develop a method for estimating local NPS from a single photon counting detector-CT (PCD-CT)acquisition. A novel nearly statistical bias-free estimator was constructed from the raw counts data of PCD-CT scan to estimate the variance of sinogram projection data. An analytical algorithm is employed to reconstruct point-wise covariance between any two image pixel/voxel locations and . A Fourier transform is applied to obtain the desired point-wise NPS for any chosen location . The method was validated using experimental data acquired from a benchtop PCD-CT system with various physical phantoms, and the results were compared with the conventional local NPS measurement method using repeated scans and statistical ensembleaveraging. The experimental results demonstrate that (1) the proposed method can achieve pointwise/local NPS measurement for a region of interest (ROI) located at any chosen position, accurately characterizing the NPS with spatial structures resulting from image content heterogeneity; (2) the local NPS measured using the proposed method show a higher precision in the measured NPS compared to the conventional measurement method; (3) spatial averaging of the local NPS yields the conventional NPS for a given localROI. A new method was developed to enable local NPS from a single PCD-CTacquisition.

Real-Time Optimal Synthetic Inversion Recovery Image Selection (RT-OSIRIS) for Deep Brain Stimulation Targeting.

Deep brain stimulation (DBS) is a method of electrical neuromodulation used to treat a variety of neuropsychiatric conditions including essential tremor, Parkinson's disease, epilepsy, and obsessive-compulsive disorder. The procedure requires precise placement of electrodes such that the electrical contacts lie within or in close proximity to specific target nuclei and tracts located deep within the brain. DBS electrode trajectory planning has become increasingly dependent on direct targeting with the need for precise visualization of targets. MRI is the primary tool for direct visualization, and this has led to the development of numerous sequences to aid in visualization of different targets. Synthetic inversion recovery images, specified by an inversion time parameter, can be generated from T1 relaxation maps, and this represents a promising method for modifying the contrast of deep brain structures to accentuate target areas using a single acquisition. However, there is currently no accessible method for dynamically adjusting the inversion time parameter and observing the effects in real-time in order to choose the optimal value. In this work, we examine three different approaches to implementing an application for real-time optimal synthetic inversion recovery image selection and evaluate them based on their ability to display continually-updated synthetic inversion recovery images as the user modifies the inversion time parameter. These methods include continuously computing the inversion recovery equation at each voxel in the image volume, limiting the computation only to the voxels of the orthogonal slices currently displayed on screen, or using a series of lookup tables with precomputed solutions to the inversion recovery equation. We find the latter implementation provides for the quickest display updates both when modifying the inversion time and when scrolling through the image. We introduce a publicly available cross-platform application built around this conclusion. We also briefly discuss other details of the implementations and considerations for extensions to other use cases.

Discovery of Alpha-1-Antichymotrypsin as a Marker of Delayed Recovery from Concussion in Children.

Of the four million children who experience a concussion each year, 30-50% of children will experience delayed recovery, where they will continue to experience symptoms more than two weeks after their injury. Delayed recovery from concussion encompasses emotional, behavioral, physical, and cognitive symptoms, and as such, there is an increased focus on developing an objective tool to determine risk of delayed recovery. This study aimed to identify a blood protein signature predictive of delayed recovery from concussion in children. Plasma samples were collected from children who presented to the Emergency Department at the Royal Children's Hospital, Melbourne, within 48h post-concussion. This study involved a discovery and validation phase. For the discovery phase, untargeted proteomics analysis was performed using single window acquisition of all theoretical mass spectra to identify blood proteins differentially abundant in samples from children with and without delayed recovery from concussion. A subset of these proteins was then validated in a separate participant cohort using multiple reaction monitoring and enzyme linked immunosorbent assay. A blood protein signature predictive of delayed recovery from concussion was modeled using a Support Vector Machine, a machine learning approach. In the discovery phase, 22 blood proteins were differentially abundant in age- and sex-matched samples from children with (n = 9) and without (n = 9) delayed recovery from concussion, six of whom were chosen for validation. In the validation phase, alpha-1-ACT was shown to be significantly lower in children with delayed recovery (n = 12) compared with those without delayed recovery (n = 28), those with orthopedic injuries (n = 7) and healthy controls (n = 33). A model consisting of alpha-1-ACT concentration stratified children based on recovery from concussion with an 0.88 area under the curve. We have identified that alpha-1-ACT differentiates between children at risk of delayed recovery from those without delayed recovery from concussion. To our knowledge, this is the first study to identify alpha-1-ACT as a potential marker of delayed recovery from concussion in children. Multi-site studies are required to further validate this finding before use in a clinical setting.

Revealing speckle obscured living human retinal cells with artificial intelligence assisted adaptive optics optical coherence tomography

BackgroundIn vivo imaging of the human retina using adaptive optics optical coherence tomography (AO-OCT) has transformed medical imaging by enabling visualization of 3D retinal structures at cellular-scale resolution, including the retinal pigment epithelial (RPE) cells, which are essential for maintaining visual function. However, because noise inherent to the imaging process (e.g., speckle) makes it difficult to visualize RPE cells from a single volume acquisition, a large number of 3D volumes are typically averaged to improve contrast, substantially increasing the acquisition duration and reducing the overall imaging throughput.MethodsHere, we introduce parallel discriminator generative adversarial network (P-GAN), an artificial intelligence (AI) method designed to recover speckle-obscured cellular features from a single AO-OCT volume, circumventing the need for acquiring a large number of volumes for averaging. The combination of two parallel discriminators in P-GAN provides additional feedback to the generator to more faithfully recover both local and global cellular structures. Imaging data from 8 eyes of 7 participants were used in this study.ResultsWe show that P-GAN not only improves RPE cell contrast by 3.5-fold, but also improves the end-to-end time required to visualize RPE cells by 99-fold, thereby enabling large-scale imaging of cells in the living human eye. RPE cell spacing measured across a large set of AI recovered images from 3 participants were in agreement with expected normative ranges.ConclusionsThe results demonstrate the potential of AI assisted imaging in overcoming a key limitation of RPE imaging and making it more accessible in a routine clinical setting.

Spatially resolved lock-in micro-thermography (SR-LIT): A tensor analysis-enhanced method for anisotropic thermal characterization

While high-throughput (HT) computations have streamlined the discovery of promising new materials, experimental characterization remains challenging and time-consuming. One significant bottleneck is the lack of an HT thermal characterization technique capable of analyzing advanced materials exhibiting varying surface roughness and in-plane anisotropy. To tackle these challenges, we introduce spatially resolved lock-in micro-thermography, an innovative technique enhanced by tensor analysis for optical thermal characterization. Our comprehensive analysis and experimental findings showcase notable advancements: We present a novel tensor-based methodology that surpasses the limitations of vector-based analysis prevalent in existing techniques, significantly enhancing the characterization of arbitrary in-plane anisotropic thermal conductivity tensors. On the instrumental side, we introduce a straightforward camera-based detection system that, when combined with the tensor-based methodology, enables HT thermal measurements. This technique requires minimal sample preparation and enables the determination of the entire in-plane thermal conductivity tensor with a single data acquisition lasting under 40 s, demonstrating a time efficiency over 90 times superior to state-of-the-art HT thermology. Additionally, our method accommodates millimeter-sized samples with poor surface finish, tolerating surface roughness up to 3.5 μm. These features highlight an innovative approach to realizing HT and accurate thermal characterization across various research areas and real-world applications.

Transport-of-intensity model for single-mask x-ray differential phase contrast imaging

X-ray phase contrast imaging holds great promise for improving the visibility of light-element materials such as soft tissues and tumors. The single-mask differential phase contrast imaging method stands out as a simple and effective approach to yield differential phase contrast. In this work, we introduce a model for a single-mask phase imaging system based on the transport-of-intensity equation. Our model provides an accessible understanding of signal and contrast formation in single-mask x-ray phase imaging, offering a clear perspective on the image formation process, for example, the origin of alternate bright and dark fringes in phase contrast intensity images. Aided by our model, we present an efficient retrieval method that yields differential phase contrast imagery in a single acquisition step. Our model gives insight into the contrast generation and its dependence on the system geometry and imaging parameters in both the initial intensity image as well as retrieved images. The model validity as well as the proposed retrieval method are demonstrated via both experimental results on a system developed in house as well as Monte Carlo simulations. In conclusion, our work not only provides a model for an intuitive visualization of image formation but also offers a method to optimize differential phase imaging setups, holding tremendous promise for advancing medical diagnostics and other applications.

Teaching a hands-on session on simultaneous Positron Emission Tomography and Magnetic Resonance image acquisition and quantification in a clinical setting

Positron Emission Tomography/Magnetic Resonance (PET/MR) imaging, is a novel imaging modality that combines the capabilities of two powerful imaging techniques in a single acquisition. This unique integration allows for simultaneous acquisition of both metabolic and structural data within a single imaging session. In this sense, PET/MR offers a comprehensive and innovative approach to medical imaging, but accompanied by its intrinsic physics and engineering complexity, involving intricate synchronization of high-performance detectors, electromagnetic shielding, and sophisticated correction algorithms, among others. In this hands-on session performed during the 6th INFIERI summer school (Madrid, Spain), we described an introduction to simultaneous PET/MR image acquisition and quantification in a real clinical to students from diverse backgrounds in physics and engineering. We first presented the fundamental aspects of PET/MR image acquisition, including the main theoretical characteristics of PET/MR physics and electronics, visiting the PET/MR facilities at Hospital Universitario HM Puerta del Sur (HM Hospitales, Móstoles, Madrid), and discussing the main PET/MR clinical and research applications. Then, we followed with a practical session on PET/MR image quantification, preparing the students to understand and solve examples on image reconstruction, multimodal data visualization, inhomogeneity correction, image registration, and attenuation correction exploiting the simplicity and usefulness of 3D Slicer.

AIRPORT: A Data Consistency Constrained Deep Temporal Extrapolation Method To Improve Temporal Resolution In Contrast Enhanced CT Imaging.

Typical tomographic image reconstruction methods require that the imaged object is static and stationary during the time window to acquire a minimally complete data set. The violation of this requirement leads to temporal-averaging errors in the reconstructed images. For a fixed gantry rotation speed, to reduce the errors, it is desired to reconstruct images using data acquired over a narrower angular range, i.e., with a higher temporal resolution. However, image reconstruction with a narrower angular range violates the data sufficiency condition, resulting in severe data-insufficiency-induced errors. The purpose of this work is to decouple the trade-off between these two types of errors in contrast-enhanced computed tomography (CT) imaging. We demonstrated that using the developed data consistency constrained deep temporal extrapolation method (AIRPORT), the entire time-varying imaged object can be accurately reconstructed with 40 frames-per-second temporal resolution, the time window needed to acquire a single projection view data using a typical C-arm cone-beam CT system. AIRPORT is applicable to general non-sparse imaging tasks using a single short-scan data acquisition.

Face anti-spoofing with cross-stage relation enhancement and spoof material perception

Face Anti-Spoofing (FAS) seeks to protect face recognition systems from spoofing attacks, which is applied extensively in scenarios such as access control, electronic payment, and security surveillance systems. Face anti-spoofing requires the integration of local details and global semantic information. Existing CNN-based methods rely on small stride or image patch-based feature extraction structures, which struggle to capture spatial and cross-layer feature correlations effectively. Meanwhile, Transformer-based methods have limitations in extracting discriminative detailed features. To address the aforementioned issues, we introduce a multi-stage CNN-Transformer-based framework, which extracts local features through the convolutional layer and long-distance feature relationships via self-attention. Based on this, we proposed a cross-attention multi-stage feature fusion, employing semantically high-stage features to query task-relevant features in low-stage features for further cross-stage feature fusion. To enhance the discrimination of local features for subtle differences, we design pixel-wise material classification supervision and add a auxiliary branch in the intermediate layers of the model. Moreover, to address the limitations of a single acquisition environment and scarcity of acquisition devices in the existing Near-Infrared dataset, we create a large-scale Near-Infrared Face Anti-Spoofing dataset with 380k pictures of 1040 identities. The proposed method could achieve the state-of-the-art in OULU-NPU and our proposed Near-Infrared dataset at just 1.3GFlops and 3.2M parameter numbers, which demonstrate the effective of the proposed method.

3D balanced SSFP UTE MRI for multiple contrasts whole brain imaging.

This study aimed to develop a new high-resolution MRI sequence for the imaging of the ultra-short transverse relaxation time (uT2) components in the brain, while simultaneously providing proton density (PD) contrast for reference and quantification. The sequence combines low flip angle balanced SSFP (bSSFP) and UTE techniques, together with a 3D dual-echo rosette k-space trajectory for readout. The expected image contrast was evaluated by simulations. A study cohort of six healthy volunteers and eight multiple sclerosis (MS) patients was recruited to test the proposed sequence. Subtraction between two TEs was performed to extract uT2 signals. In addition, conventional longitudinal relaxation time (T1) weighted, T2-weighted, and PD-weighted MRI sequences were also acquired for comparison. Typical PD-contrast was found in the second TE images, while uT2 signals were selectively captured in the first TE images. The subtraction images presented signals primarily originating from uT2 components, but only if the first TE is short enough. Lesions in the MS subjects showed hyperintense signals in the second TE images but were hypointense signals in the subtraction images. The lesions had significantly lower signal intensity in subtraction images than normal white matter (WM), which indicated a reduction of uT2 components likely associated with myelin. 3D isotropic sub-millimeter (0.94 mm) spatial resolution images were acquired with the novel bSSFP UTE sequence within 3 min. It provided easy extraction of uT2 signals and PD-contrast for reference within a single acquisition.