Differential Imaging Research Articles

New geometrid moths from Iraqi Kurdistan (Lepidoptera, Geometridae: Sterrhinae, Larentiinae).

A large number of geometrid moths was collected by the first author in Iraqi Kurdistan including several undescribed species and subspecies. In this paper we describe three new geometrid taxa: Idaea medianocturna walaila ssp. nov., Lulavia mahwii sp. nov. and Protorhoe drechseli nebuloides ssp. nov. We present differential diagnoses and images of adult moths and genitalia.

On the effect of precession for magnetic differential phase contrast imaging

The separation of diffraction effects from phase contrast is a major challenge for differential phase contrast (DPC) imaging in scanning transmission electron microscopy (STEM). The application of electron beam precession has previously been proven successful in homogenizing the direct beam and improving the imaging of both long-range electric and magnetic fields. However, magnetic STEM-DPC imaging performed in a low magnification (LM) STEM mode suffers from significant aberrations of the probe forming lens and the consequent impediment of small precession angles. By investigating the application of precession path segmentation to LM-STEM precessed scans for the imaging of LSMO and FeAl thin film samples, the initially reported benefits of precession were discovered to be less substantial than originally assumed. The segmentation methodology reveals that precession induced beam phase shifts account for a large part of the DPC induction profile smoothing, and the precession path is non-circular, leading to streaking artifacts in the reconstructed induction maps.

High strehl and high contrast for the ELT instrument METIS

The Mid-infrared ELT Imager and Spectrograph (METIS) is a first-generation instrument for the Extremely Large Telescope (ELT), Europe’s next-generation 39 m ground-based telescope for optical and infrared wavelengths, which is currently under construction at the European Southern Observatory (ESO) site at Cerro Armazones in Chile. METIS will offer diffraction-limited imaging, low- and medium-resolution slit spectroscopy, and coronagraphy for high-contrast imaging between 3 and 13 microns, as well as high-resolution integral field spectroscopy between 3 and 5 microns. The main METIS science goals are the detection and characterisation of exoplanets, the investigation of proto-planetary disks, and the formation of planets. The Single-Conjugate Adaptive Optics (SCAO) system corrects atmospheric distortions and is thus essential for diffraction-limited observations with METIS. SCAO will be used for all observing modes, with high-contrast imaging imposing the most demanding requirements on its performance. The Final Design Review (FDR) of METIS took place in the fall of 2022; the development of the instrument, including its SCAO system, has since entered the Manufacturing, Assembly, Integration and Testing (MAIT) phase. Numerous challenging aspects of an ELT Adaptive Optics (AO) system are addressed in the mature designs for the SCAO control system and the SCAO hardware module: the complex interaction with the telescope entities that participate in the AO control, wavefront reconstruction with a fragmented and moving pupil, secondary control tasks to deal with differential image motion, non-common path aberrations and mis-registration. A K-band pyramid wavefront sensor and a GPU-based Real-Time Computer (RTC), tailored to the needs of METIS at the ELT, are core components. This current paper serves as a natural sequel to our previous work presented in Hippler et al. (2018). It reflects all the updates that were implemented between the Preliminary Design Review (PDR) and FDR, and includes updated performance estimations in terms of several key performance indicators, including achieved contrast curves. We outline all important design decisions that were taken, and present the major challenges we faced and the main analyses carried out to arrive at these decisions and eventually the final design. We also elaborate on our testing and verification strategy, and, last not least, comprehensively present the full design, hardware and software in this paper to provide a single source of reference which will remain valid at least until commissioning.

Evaluating the reproducibility of a deep learning algorithm for the prediction of retinal age.

Recently, a deep learning algorithm (DLA) has been developed to predict the chronological age from retinal images. The Retinal Age Gap (RAG), a deviation between predicted age from retinal images (Retinal Age, RA) and chronological age, correlates with mortality and age-related diseases. This study evaluated the reliability and accuracy of RA predictions and analyzed various factors that may influence them. We analyzed two groups of participants: Intravisit and Intervisit, both imaged by color fundus photography. RA was predicted using an established algorithm. The Intervisit group comprised 26 subjects, imaged in two sessions. The Intravisit group had 41 subjects, of whom each eye was photographed twice in one session. The mean absolute test-retest difference in predicted RA was 2.39years for Intervisit and 2.13years for Intravisit, with the latter showing higher prediction variability. The chronological age was predicted accurately from fundus photographs. Subsetting image pairs based on differential image quality reduced test-retest discrepancies by up to 50%, but mean image quality was not correlated with retest outcomes. Marked diurnal oscillations in RA predictions were observed, with a significant overestimation in the afternoon compared to the morning in the Intravisit cohort. The order of image acquisition across imaging sessions did not influence RA prediction and subjective age perception did not predict RAG. Inter-eye consistency exceeded 3years. Our study is the first to explore the reliability of RA predictions. Consistent image quality enhances retest outcomes. The observed diurnal variations in RA predictions highlight the need for standardized imaging protocols, but RAG could soon be a reliable metric in clinical investigations.

SURGICAL RESECTION OF A COMPLEX TUBERCULUM SELLAE MENINGIOMA ENCASING MAJOR ARTERIES

Introduction Though constituting only a minor proportion (1%) of sellar masses, suprasellar meningiomas pose a significant diagnostic challenge within the region of sellar and suprasellar tumors. Pituitary adenomas, at nearly 90% prevalence, dominate this anatomical region. Distinguishing these two entities is paramount, as both clinical presentation and, to some extent, biochemical profiles exhibit notable overlap. Accurate preoperative differentiation is critical due to the contrasting behaviors of these tumors. Meningiomas, with their robust vascularity supplied by dural and osseous arteries, present a heightened risk of intraoperative hemorrhage. Clinical Case A 53-year-old woman presented with a two-month history of worsening headaches and gradual vision loss. Neurological examination revealed only visual acuity decline. Her hormone profile showed elevated prolactin but lacked clinical features of prolactin excess, suggesting a possible prolactin-secreting pituitary macroadenoma. A contrast-enhanced MRI confirmed a significant sellar and suprasellar mass with homogeneous enhancement, extending to the right paramedian region and encasing the right internal carotid artery (ICA) at its critical segment involving the cavernous and supraclinoid portions. Furthermore, the right middle meningeal artery (M1) and anterior cerebral artery (A1) originated from this same location, highlighting the high surgical risk. Surgical resection was deemed necessary. The patient underwent a right pterional craniotomy, revealing a grayish, extradural soft mass lesion encasing the ICA bifurcation. Careful microsurgical dissection with basal devascularization was performed, followed by near-complete tumor removal using an ultrasonic aspirator to minimize damage to the encased arteries. Postoperative follow-up CT scan confirmed successful near-total tumor ablation. Conclusion This case underscores the critical role of meticulous preoperative diagnosis in managing complex sellar tumors. While pituitary adenomas dominate this region, suprasellar meningiomas, despite their rarity, demand a high index of suspicion. Overlapping clinical and biochemical presentations highlight the reliance on advanced imaging for accurate differentiation. The intricate vascularity of meningiomas, as exemplified by the encasement of critical arteries in this case, necessitates meticulous surgical technique with devascularization strategies. This successful near-complete tumor removal emphasizes the importance of such surgical expertise in navigating these diagnostically challenging sellar lesions.

Single-shot quantitative differential phase contrast microscope using a single calcite beam displacer

This paper presents the development of a single-shot, partially spatially coherent quantitative differential phase contrast microscopy (Q-DPCM) system. The optical scheme comprises a polarizer, lenses, calcite beam displacer, and analyzer, which can be seamlessly integrated to an existing bright-field microscopy system, transforming it into a Q-DPCM system. It utilizes a partially spatially coherent light source, enabling single-shot quantitative differential phase recovery of the specimens with high spatial phase sensitivity. It generates highly sensitive quantitative differential phase images of the specimens along one direction, like a gradient light interference microscopy (GLIM) system, using only a single interferogram. First, we validated the differential phase measurement capability of the system through experiments on polystyrene spheres (diameter 5.2 µm) and HeLa cells. Next, the system is utilized to generate quantitative phase maps of human red blood cells using two orthogonal differential interferograms recorded at two orientations of the calcite beam displacer. Further, the Q-DPCM system is implemented for 1-h time-lapse live cell monitoring, revealing the dynamics of intracellular granules such as nucleolus and lipids in U2OS cells.

Deep Search for a Scattered Light Dust Halo Around Vega with the Hubble Space Telescope

We present a provisory scattered-light detection of the Vega debris disk using deep Hubble Space Telescope (HST) coronagraphy (PID 16666). At only 7.7 pc, Vega is immensely important in debris disk studies both for its prominence and also because it allows the highest physical resolution among all debris systems relative to temperature zones around the star. We employ the STIS coronagraph’s widest wedge position and classical reference differential imaging to achieve among the lowest surface-brightness sensitivities to date ( ∼4μJyarcsec−2 ) at wide separations using 32 orbits in Cycle 29. We detect a halo extending from the inner edge of our effective inner working angle at 10.″5 out to the photon noise floor at 30″ (80–230 au). The face-on orientation of the system and the lack of a perfectly color-matched point-spread function star have posed significant challenges to the reductions, particularly regarding artifacts from the imperfect color matching. However, we find that a halo of small dust grains provides the best explanation for the observed signal. Unlike Fomalhaut (a close twin to Vega in luminosity, distance, and age), there is no clear distinction in scattered light between the parent planetesimal belt observed with the Atacama Large Millimeter/submillimeter Array and the extended dust halo. These HST observations complement JWST GTO Cycle 1 observations of the system with NIRCam and MIRI.

Radiomics analysis in differentiating osteosarcoma and chondrosarcoma based on T2-weighted imaging and contrast-enhanced T1-weighted imaging

This study was performed to investigate the diagnostic value of radiomics models constructed by fat suppressed T2-weighted imaging (T2WI-FS) and contrast-enhanced T1-weighted imaging (CET1) based on magnetic resonance imaging (MRI) for differentiation of osteosarcoma (OS) and chondrosarcoma (CS). In this retrospective cohort study, we included all inpatients with pathologically confirmed OS or CS from Second Xiangya Hospital of Central South University (Hunan, China) as of October 2020. Demographic and imaging variables were extracted from electronic medical records and compared between OS and CS group. Totals of 530 radiomics features were extracted from CET1 and T2WI-FS sequences based on MRI. The least absolute shrinkage and selection operator (LASSO) method was used for screening and dimensionality reduction of the radiomics model. Multivariate logistic regression analysis was performed to construct the radiomics model, and receiver operating characteristic curve (ROC) was generated to evaluate the diagnostic accuracy of the radiomics model. The training cohort and validation cohort included 87 and 29 patients, respectively. 8 CET1 features and 15 T2WI-FS features were screened based on the radiomics features. In the training group, the area under the receiver-operator characteristic curve (AUC) value for CET1 and T2WI-FS sequences in the radiomics model was 0.894 (95% CI 0.817–0.970) and 0.970 (95% CI 0.940–0.999), respectively. In the validation group, the AUC value for CET1 and T2WI-FS sequences in the radiomics model was 0.821 (95% CI 0.642–1.000) and 0.899 (95% CI 0.785–1.000), respectively. In this study, we developed a radiomics model based on T2WI-FS and CET1 sequences to differentiate between OS and CS. This model exhibits good performance and can help clinicians make decisions and optimize the use of healthcare resources.

Unveiling sulfur vacancy pairs as bright and stable color centers in monolayer WS2

Color centers, arising from zero-dimensional defects, exploit quantum confinement to access internal electron quantum degrees of freedom, holding potential for quantum technologies. Despite intensive research, the structural origin of many color centers remains elusive. In this study, we employ in-situ cathodoluminescence scanning transmission electron microscopy combined with integrated differential phase contrast imaging to examine how defect configuration in tungsten sulfide determines color-center emission. Using an 80-kV accelerated electron beam, defects were deliberately produced, visualized, excited in situ and characterized in real time in monolayer WS2 within hBN|WS2 | hBN heterostructures at 100 K. These color centers were simultaneously measured by cathodoluminescence microscopy and differentiated by machine learning. Supported by DFT calculations, our results identified a crucial sulfur vacancy configuration organized into featured vacancy pairs, generating stable and bright luminescence at 660 nm. These findings elucidate the atomic-level structure-exciton relationship of color centers, advancing our understanding and quantum applications of defects in 2D materials.

Multiple reference star differential imaging with VLT/SPHERE

Context. High-contrast imaging observations mostly rely on angular differential imaging, a successful technique for detecting point-sources, such as planets. However, in the vicinity of the star (typically below 300 mas), this technique suffers from signal self-subtraction when there is not enough field rotation. Building large libraries of reference stars from archival data later used to optimally subtract the stellar halo is a powerful technique known as reference star differential imaging (RSDI) that can overcome this limitation. Aims. We aim at investigating new methods for creating reference libraries composed of multiple stars when applying reference star differential imaging to VLT/SPHERE data. We used for that purpose a data set from the SPHERE High Angular Resolution Debris Disk Survey (SHARDDS), composed of 55 targets observed in broad-band H with the InfraRed Dual-band Imager and Spectrograph (IRDIS) during 2015-2016, with a total of ~20 000 frames. We consider HD 206893, known to host a close-in bound substellar companion HD 206893 B, as a benchmark science target to demonstrate the improved sensitivity provided by this method. Methods. We created libraries of reference frames based on different image similarity metrics: the cosine distance between descriptors created by a convolutional neural network, the Pearson correlation coefficient, the Structural Similarity Index, the Strehl ratio, and raw contrast criteria. We used principal component analysis (PCA) to subtract the stellar halo and tested various normalization options. Results. We obtained the best signal-to-noise ratio (S/N) on HD 206893 B by using the Pearson correlation coefficient (PCC) applied to an annulus between 245 and 612 mas to select reference frames. The ten reference libraries with the highest S/N on the substellar companion HD 206893 B were all based on the PCC method, outperforming other similarity metrics. While the Strehl ratio is the environment variable most correlated to the contrast, it is insufficient to select similar images. We also show that having multiple reference stars in the reference library produces better results than using a single well-chosen reference star. Conclusions. Using the Pearson correlation computed on a specific area of interest to select reference frames is a promising alternative to improve the detectability of faint point-sources when applying reference star differential imaging. In the future, reducing all the data available in the SPHERE archive using this technique might offer interesting results in the search for previously undetected planets.

Transport-of-intensity differential phase contrast imaging: defying weak object approximation and matched-illumination condition

Quantitative phase imaging (QPI) has emerged as a promising label-free imaging technique with growing importance in biomedical research, optical metrology, materials science, and other fields. Partially coherent illumination provides resolution twice that of the coherent diffraction limit, along with improved robustness and signal-to-noise ratio, making it an increasingly significant area of study in QPI. Partially coherent QPI, represented by differential phase contrast (DPC), linearizes the phase-to-intensity transfer process under the weak object approximation (WOA). However, the nonlinear errors caused by WOA in DPC can lead to phase underestimation. Additionally, DPC requires strict matching of the illumination numerical aperture (NA) to ensure the complete transmission of low-frequency information. This necessitates precise alignment of the optical system and limits the flexible use of objective and illumination. In this study, the applicability of the WOA under different coherence parameters is explored, and a method to defy WOA by reducing the illumination NA is proposed. The proposed method uses the transport-of-intensity equation through an additional defocused intensity image to recover the lost low-frequency information due to illumination mismatch, without requiring any iterative procedure. This method overcomes the limitations of DPC being unable to recover large phase objects and does not require the strict illumination matching conditions. The accurate quantitative morphological characterization of customized artifact and microlens arrays that do not satisfy WOA under non-matched-illumination conditions demonstrated the precise quantitative capability of the proposed method and its excellent performance in the field of measurement. Meanwhile, the phase retrieval of tongue slices and oral epithelial cells demonstrated its application potential in the biomedical field. The ability to accurately recover phase under a concise and implementable optical setup makes it a promising solution for widespread application in various label-free imaging domains.

MTCSNet: One-Stage Learning and Two-Point Labeling are Sufficient for Cell Segmentation.

Deep convolution neural networks have been widely used in medical image analysis, such as lesion identification in whole-slide images, cancer detection, and cell segmentation, etc. However, it is often inevitable that researchers try their best to refine annotations so as to enhance the model performance, especially for cell segmentation task. Weakly supervised learning can greatly reduce the workload of annotations, while there is still a huge performance gap between the weakly and fully supervised learning approaches. In this work, we propose a weakly-supervised cell segmentation method, namely Multi-Task Cell Segmentation Network (MTCSNet), for multi-modal medical images, including pathological, brightfield, fluorescent, phase-contrast and differential interference contrast images. MTCSNet is learnt in a single-stage training manner, where only two annotated points for each cell provide supervision information, and the first one is the centroid, the second one is its boundary. Additionally, five auxiliary tasks are elaborately designed to train the network, including two pixel-level classifications, a pixel-level regression, a local temperature scaling and an instance-level distance regression task, which is proposed to regress the distances between the cell centroid and its boundaries in eight orientations. The experimental results indicate that our method outperforms all state-of-the-art weakly-supervised cell segmentation approaches on public multi-modal medical image datasets. The promising performance also shows that a single-stage learning with two-point labeling approach are sufficient for cell segmentation, instead of fine contour delineation. The codes are available at: https://github.com/binging512/MTCSNet.

Diagnostic Accuracy of Preoperative Imaging for Differentiation of Branch Duct Versus Mixed Duct Intraductal Papillary Mucinous Neoplasms: Erratum.

Diagnostic Accuracy of Preoperative Imaging for Differentiation of Branch Duct Versus Mixed Duct Intraductal Papillary Mucinous Neoplasms: Erratum.

Temporal and chromatic variation of polarized scattered light in the outer disk of PDS 70

PDS 70 stands out as the only system hosting a protoplanetary disk and two confirmed planets undergoing formation. It is a unique target for characterizing the dust in this type of disk. We aim to accurately measure the reflected polarized intensity and quantify the variability and asymmetry for PDS 70 across multiple epochs and wavelengths in the optical and near-infrared. We present new high-contrast polarimetric differential imaging observations of PDS 70, with the $N\_R$ filter on SPHERE/ZIMPOL. We combined the new observation with archival data of the VLT/SPHERE instrument, spanning five wavelengths ($N\_R$, $VBB$, $J$, $H$, and $Ks$) over seven epochs and eight years. For each observational epoch, we corrected the smearing effect due to finite instrument resolution, measured the azimuthal brightness profiles, and derived the intrinsic disk-integrated polarized reflectivity and the intrinsic brightness contrasts. With our homogeneous analysis of all available optical and near-infrared data sets of the disk around PDS 70, we find significant temporal variability of the integrated polarized reflectivity as well as the azimuthal brightness profile. This indicates variable shadowing on the outer disk by inner disk structures beyond the resolution limit of current imaging instruments. Despite these variabilities, we observe a systematic wavelength-dependent contrast between the near side and the far side of the inclined disk. These results underline the importance of considering both the shadowing effect from the inner disk and the surface geometry of the observed reflecting disk in the analysis and interpretation of observational data.

VLT/MUSE Detection of Accretion/Ejection Associated with the Close Stellar Companion in the HT Lup System

The accretion/ejection processes in T Tauri stars are fundamental to their physical evolution, while also impacting the properties and evolution of the circumstellar material at a time when planet formation takes place. To date, the characterization of ongoing accretion processes in stellar pairs at 5–50 au scales has been challenging as high-angular resolution spectrographs are required to extract the spectral features of each component. We present the analysis of spectroscopic observations of the tight (160 mas, 25 au) T Tauri system HT Lup A/B, obtained with MUSE at the Very Large Telescope in 2021 March and July. We focus on constraining the accretion/ejection processes and variability of the secondary component HT Lup B by searching for accretion tracers by applying high-resolution spectral differential imaging techniques. We retrieve strong (signal-to-noise ratio > 5) Hα, Hβ, and [O i]λ6300 emission in both epochs. The Hα and Hβ line fluxes showcase high variability, with variations up to 200%–300% between epochs. The fluxes are consistent with accretion rates of 3× 10−9 M ⊙ yr−1 and 8 × 10−10 M ⊙ yr−1 for the first and second epochs, respectively. We attribute the increased accretion activity during the first night to a “burst-like” event, followed by a relaxation period more representative of the common accretion activity of the system. The [O i]λ6300 line profiles remain relatively similar between epochs and suggest ejection rates on the order of 10−9−10−10 M ⊙ yr−1, compatible with moderate disk wind emission. Our results also indicate that the accretion processes of HT Lup B are compatible with Classical T Tauri stars, unlike previous classifications.

Clustering analysis based on clinically available data for improving risk stratification and outcome prediction of hypertension

Abstract Background Hypertension (HTN) is a heterogeneous condition with several factors contributing to adverse outcomes. Machine learning can harness complex data to unveil outcome predictors and guide prevention. Purpose To use clustering analysis on clinical data to identify HTN risk profiles and their associations with cardiovascular abnormalities and clinical outcomes. Methods A cohort of 14,840 UK Biobank hypertensive participants without pre-existing heart failure (HF) who underwent cardiovascular magnetic resonance (CMR) assessment was examined using K-means clustering on 79 clinical attributes. The clusters’ association with incident HF, mortality, atrial fibrillation (AF), and major adverse cardiovascular events (MACE) were evaluated, alongside imaging characteristics, with mediation analysis probing the role of imaging in risk differentiation. All post-hoc analyses were adjusted for vascular risk factors (VRFs), including diabetes, hypercholesterolaemia, previous myocardial infarction. Results Three distinct clusters differing considerably in lifestyle habits, cardiovascular risk factors, electrocardiographic parameters, and cardiometabolic profiles were identified. Cluster 1 (lowest risk), predominantly females, exhibited the most favourable metabolic profile and outcomes. Cluster 2 (highest risk), predominantly males, had the most adverse metabolic and cardiovascular profiles, and the highest risk of all adverse outcomes, especially AF and HF (hazard ratio (HR) 1.80 [1.45–2.25] and 1.85 [1.39–2.46]; p <0.005). This group was associated with more eccentric LV hypertrophy (LVH), overall poorer left atrial emptying function (LAEF), bi-ventricular systolic function and LV mechanics, and higher systemic vascular resistance (Figure 1). Cluster 3 (intermediate risk) was a more heterogeneous group with the highest burden of diabetes and adiposity and a moderate rise in AF and MACE risk (HR 1.61 [1.12-2.32] and 1.30 [1.07-1.58]; p <0.05). This cluster was associated with concentric LV remodelling and better indices of cardiac mechanics, but greater impairment in LA booster pump function (active LAEF) than Cluster 2 (Figure 1). Cluster 2's effect on MACE was mostly mediated through LV mass increase (proportion mediated, 67%), followed by changes (reducing) in LV global longitudinal strain (33%), and ejection fraction (25.4%). The indirect effect of CMR changes in the association between cluster 3 and MACE was much smaller with the highest proportion of the effects mediated through increased myocardial wall thickness (26%) but not LV mass, and changes in all the components of LA function. Conclusions Clinical data clustering provides insight into distinct HTN risk profiles, each with specific imaging characteristics and clinical trajectories, hinting at different pathophysiological mechanisms. Enhanced phenotyping can facilitate tailored interventions based on the disease subtype and improve clinical outcomes.Figure 1.

Underwater image restoration via spatially adaptive polarization imaging and color correction

Polarization imaging is extensively employed in underwater image restoration owing to its effectiveness in eliminating backscattered light. However, the existing polarization-based imaging methods rely on the strong assumption that the degrees of polarization (DoPs) of the target and backscattered light remain constant. Additionally, these methods ignore wavelength-specific absorption phenomena. To address these challenges, we propose an underwater image restoration method via spatially adaptive polarization imaging and color correction. First, based on optimal polarization difference images, we propose a method for calculating the spatial DoP of the target. In this method, the polarization characteristics of the target and background are fully exploited, and a scoring function is designed to achieve an optimal differential image. Second, we propose an adaptive local optimization method to estimate the spatial DoP of backscattering, which involves dividing the image into multiple local regions, and then employing improved particle swarm optimization (IPSO) algorithms to obtain the optimal value of DoP for each region. Finally, we introduce an adaptive compensation method based on the channel with minimal color absorption to correct color shifts during underwater polarization imaging. Extensive experiments demonstrate that our method exhibits superior generalization capability and outstanding restoration performance compared to existing methods.

Static X-ray differential phase contrast imaging via bidirectional-misalignment grating

Grating-based X-ray differential phase contrast imaging (GB-DPCI) offers excellent imaging contrast for soft tissues. Limited by the phase stepping of gratings, the conventional GB-DPCI leads to a high radiation dose. This study presents a static GB-DPCI method employing an analyzer grating with a misaligned structure in both vertical and horizontal directions. A signal retrieval algorithm is developed for this method to permit the use of neighboring pixels on the detector to approximate multiple phase stepping positions, thereby obtaining the phase contrast signal in a single exposure. This study reduces high radiation doses and time-consumption caused by phase stepping. The presented method is validated with datasets from a laboratory X-ray tube and synchrotron radiation. Considering synchrotron results as example, minimal improvements in Feature Similarity Index Measure are 2.48%, 6.31%, and 7.06% for absorption, dark field, and phase contrasts, and in Information-Weight Structure Similarity Index Measure are 3.24%, 16.07%, and 8.61%.

REXPACO ASDI: joint unmixing and deconvolution of the circumstellar environment by angular and spectral differential imaging

ABSTRACT Angular and spectral differential imaging is an observational technique of choice to investigate the immediate vicinity of stars. By leveraging the relative angular motion and spectral scaling between on-axis and off-axis sources, post-processing techniques can separate residual star light from light emitted by surrounding objects such as circumstellar discs or point-like objects. This paper introduces a new algorithm that jointly unmixes these components and deconvolves disc images. The proposed algorithm is based on a statistical model of the residual star light, accounting for its spatial and spectral correlations. These correlations are crucial yet remain inadequately modelled by existing reconstruction algorithms. We employ dedicated shrinkage techniques to estimate the large number of parameters of our correlation model in a data-driven fashion. We show that the resulting separable model of the spatial and spectral covariances captures very accurately the star light, enabling its efficient suppression. We apply our method to data sets from the Very Large Telescope/Spectro-Polarimetry High-contrast Exoplanet REsearch instrument and compare its performance with standard algorithms (median subtraction, PCA, PACO). We demonstrate that considering the multiple correlations within the data significantly improves reconstruction quality, resulting in better preservation of both disc morphology and photometry. With its unique joint spectral modelling, the proposed algorithm can reconstruct discs with circular symmetry (e.g. rings, spirals) at intensities one million times fainter than the star, without needing additional reference data sets free from off-axis objects.

Comparison between Magnetic Resonance Elastography and Diffusion-Weighted Imaging in Differentiation of Benign and Malignant Hepatic Focal Lesions

Abstract Background With the widespread use of cross-sectional imaging techniques, the detection of focal liver lesions (FLLs) has become increasingly common. Many FLLs are incidental, and characterization with imaging is an effective means to reduce the need for invasive biopsies for histological confirmation. Objective To compare between MRE and diffusion–weighted imaging for differentiating benign and malignant hepatic focal lesions. Methods This Prospective study was conducte at department of Radiodiagnosis of National Hepatology and Tropical Medicine Research Institute “NHTMRI” in Cairo, Egypt, on 50 patients. Results Our study results revealed that in the comparison between diffusion and MRE to detect malignant lesions, the sensitivity and specificity of diffusion was 100% and 40.9% respectively, but for MRE was 89.3% and 100%, Also showed that MRE is significantly superior to DWI for distinguishing between malignant and benign FLLs, with 89% sensitivity, 100% specificity, and accuracy for MRE. Among all FLLs. the most frequent focal lesion HCC by 48.0% followed by hemangioma and inflammatory lesions by 26% & 12% respectively. Conclusion MRE provides a non-invasive quantitative parameter that may be useful for differentiating common benign and malignant FLLs. MRE performed better than DWI, and shows great promise as a non-invasive alternative to biopsy for the differentiation of benign and malignant FLLs and demonstrates additive value to conventional imaging. However, there is opportunity for further enhancement of the technique, particularly with regard to optimization of image quality and evaluation of smaller FLLs.