Deep learning at the edge enables real-time streaming ptychographic imaging.

Coherent imaging techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells. Driven by the construction of brighter sources and high-rate detectors, coherent imaging methods like ptychography are poised to revolutionize nanoscale materials characterization. However, these advancements are accompanied by significant increase in data and compute needs, which precludes real-time imaging, feedback and decision-making capabilities with conventional approaches. Here, we demonstrate a workflow that leverages artificial intelligence at the edge and high-performance computing to enable real-time inversion on X-ray ptychography data streamed directly from a detector at up to 2 kHz. The proposed AI-enabled workflow eliminates the oversampling constraints, allowing low-dose imaging using orders of magnitude less data than required by traditional methods.

Validation of Computerized Quantification of Ocular Redness.

PURPOSE: To show feasibility of computerized techniques for ocular redness quantification in clinical studies, and to propose an automatic, objective method. METHODS: Software for quantification of redness of the bulbar conjunctiva was developed. It provides an interface for manual and automatic sclera segmentation along with automated alignment of region of interest to enable estimation of changes in redness. The software also includes the redness scoring methods: (1) contrast-limited adaptive histogram equalization (CLAHE) in red-green-blue (RGB) color model, (2) product of saturation and hue in hue-saturation-value (HSV), and (3) average of angular sections in HSV. Our validation pipeline compares the scoring outcomes from the perspectives of segmentation reliability, segmentation precision, segmentation automation, and the choice of redness scoring methods. RESULTS: Ninety-two photographs of eyes before and after provoked redness were evaluated. Redness in manually segmented images was significantly different within human observers (interobserver, P = 0.04) and two scoring sessions (intraobserver, P < 0.001). Automated segmentation showed the smallest variability, and can therefore be seen as a robust segmentation method. The RGB-based scoring method was less sensitive in redness assessment. CONCLUSIONS: Computation of ocular redness depends heavily on sclera segmentation. Manual segmentation appears to be subjective, resulting in systematic errors in intraobserver and interobserver settings. At the same time, automatic segmentation seems to be consistent. The scoring methods relying on HSV color space appeared to be more consistent. TRANSLATIONAL RELEVANCE: Computerized quantification of ocular redness holds great promise to objectify ocular redness in the standard clinical care and, in particular, in clinical trials.

Removal of simulated biofilm at different implant crown designs with interproximal oral hygiene aids: An in vitro study.

OBJECTIVES: To compare the removal of simulated biofilm at two different implant-supported restoration designs with various interproximal oral hygiene aids. METHODS: Mandibular models with a missing first molar were fabricated and provided with single implant analogues (centrally or distally placed) and two different crown designs (conventional [CCD] and alternative crown design [ACD]). Occlusion spray was applied to the crowns to simulate artificial biofilm. Thirty participants (dentists, dental hygienists, and laypersons) were equally divided and asked to clean the interproximal areas with five different cleaning devices to further evaluate if there were differences in their cleaning ability. The outcome was measured via standardized photos and the cleaning ratio, representing the cleaned surfaces in relation to the respective crown surface. Statistical analysis was performed by linear mixed-effects model with fixed effects for cleaning tools, surfaces, crown design and type of participant, and random effects for crowns. RESULTS: The mean cleaning ratio for the investigated tools and crown designs were (in%): Super floss: 76 ± 13/ACD and 57 ± 14/CCD (highest cleaning efficiency), followed by dental floss: 66 ± 13/ACD and 56 ± 15/CCD, interdental brush: 55 ± 10/ACD and 45 ± 9/CCD, electric interspace brush: 31 ± 10/ACD and 30 ± 1/CCD, microdroplet floss: 8 ± 9/ACD and 9 ± 8/CCD. There was evidence of an overall effect of each factor "cleaning tool," "surface," "crown design," and "participant" (p < 0.0001). CONCLUSIONS: ACD allowed more removal of the artificial biofilm than CCD with Super floss, dental floss, and interdental brush. Flossing and interproximal brushing were the most effective cleaning methods. A complete removal of the artificial biofilm could not be achieved in any group.

Quantitative light-induced fluorescence images and digital photographs - Reproducibility of manually marked demineralisations.

OBJECTIVE: Hard tooth tissue demineralisation is an undesirable side effect of orthodontic treatment with fixed appliances. Whereas both clinically and in digital photographs (DP), demineralisations appear as white spot lesions, WSLs appear as dark areas when quantitative light-induced fluorescence (QLF) imaging is used. This study aims at comparing the reproducibility of the detection of decalcified tooth areas in DP and QLF. MATERIALS AND METHODS: DP and QLF pairs were acquired from 139 teeth of 32 patients after braces removal. Three raters manually marked the decalcified area on both DP and QLF images. The markings were repeated after 2 weeks. A ground truth was estimated for each tooth and modality using the simultaneous truth and performance level estimation (STAPLE) algorithm. The Dice coefficients (DC) of each rater marking to the ground truth were calculated for all teeth and modalities to quantify the spatial agreement. A three-way repeated measures analysis of variance (ANOVA) was used to compare the means of the DCs for both modalities ([Formula: see text]). Intra-observer and intercycle variabilities were assessed comparing the means across the raters and the cycles for both modalities. RESULTS: ANOVA revealed a statistical significant difference between the modalities [[Formula: see text], [Formula: see text]]. The standard deviation of the DC for the photographs are lower than those for the QLF images. Intra-observer and intercycle differences are rather small as compared to the intermodality differences. CONCLUSIONS: The results indicate a higher spatial reproducibility in identifying a decalcified area on a tooth surface using visual inspection of DP rather than QLF images.

3D Documentation of Chronic Wounds Using Low-Cost Mobile Devices.

The state-of-the-art wound assessment is manually performed by clinicians. This is ineffective and imprecise. Special devices have been developed for automation, but they are expensive and often lack portability. We present a concept of a low-cost system for wound documentation and analysis. Using computer vision techniques, 3D reconstructions of wounds can be created from images taken with a simple camera, such as those embedded in mobile phones.