Nonlinear approximation of wildfire front temperature on MODIS data for sub-pixel analysis of burning

An improved approach to evaluate thermal anomalies characteristics using the pixel-based analysis of the MODIS imagery was proposed. The approach allows us to improve the accuracy in estimating characteristics of active combustion zones comparing to the standard Dozier method. We used the imagery of active wildfires in Siberian forests from the MODIS radiometer acquired in the spectral ranges of 3.930–3.990 and 10.780–11.280 mm (bands 21 and 31, respectively). Nonlinear exponential function was used to describe the approximation of the temperature of combustion zones. Available data of field and numerical experiments were used for validating of the approximation accuracy. Nonlinear approximation of wildfire front temperature allows to determine the portion of the active pixel of the MODIS image with the given temperature excess comparing to the temperature of background cover. This improves the accuracy in extracting of active burning zones as well as in classifying the heat release rate at the sub-pixel level of analysis.

Abstract 1122‐000211: Histology Profiles of Thrombi in Men and Women Undergoing Thrombectomy

Introduction : Understanding clot composition and associated genomic, epigenomic, and proteomic signatures could provide insight into thrombus biology and etiology, and aid in prognosis in stroke. We report preliminary analysis of histology evaluations in subjects enrolled in the INSIGHT Registry, a multicentered ‘multi‐omic’ analysis of thrombi associated with acute hemorrhagic and ischemic stroke this multi‐omic clot collection registry. Our aim was to determine potential histology differences between men and women with emergent large vessel occlusive thrombi. Methods : Subjects age ≥18 years, treated frontline with the Penumbra System® for thrombectomy are included in this analysis. Patient demographics, medical history, radiographic, and procedural information are collected in conjunction with extracted clot and concurrent extracranial arterial blood. Enrollment, data collection and monitoring are ongoing for the INSIGHT registry. While the protocol include analysis for proteomics and transcriptomics, for this analysis we used automated histology. An MSB Trichrome stain was used to evaluate the tissue. Composition was determined by automated pixel analysis, with the values representing ratios of the overall clot. Results : Samples from 60 subjects were enrolled from 10 sites between 02/2021 and 07/2021. Analysis of the thrombi determined the relative proportions of fibrin, red blood cells (RBCs), and platelets (PLT). The median RBC‐fibrin ratio did not differ between females (1.27, IQR 0.57‐2.62) n = 34 and males (0.95, IQR 0.41‐1.51) n = 26. However, the ratio was more widely distributed in females as seen in the wider IQR. Conclusions : These preliminary results demonstrate a lack of uniform differences in thrombus composition in males versus females with emergent large vessel occlusion. There may be more heterogeneity among females, which requires further study.

Spatio-Temporal Mixed Pixel Analysis of Savanna Ecosystems: A Review

Reliable estimates of savanna vegetation constituents (i.e., woody and herbaceous vegetation) are essential as they are both responders and drivers of global change. The savanna is a highly heterogenous biome with high variability in land cover types while also being very dynamic at both temporal and spatial scales. To understand the spatial-temporal dynamics of savannas, using Earth Observation (EO) data for mixed-pixel analysis is crucial. Mixed pixel analysis provides detailed land cover data at a sub-pixel level which are essential for conservation purposes, understanding food supply for herbivores, quantifying environmental change, such as bush encroachment, and fuel availability essential for understanding fire dynamics, and for accurate estimation of savanna biomass. This review paper consulted 197 studies employing mixed-pixel analysis in savanna ecosystems. The review indicates that studies have so far attempted to resolve the savanna mixed-pixel issues by using mainly coarse resolution data, such as Terra-Aqua MODIS and AVHRR and medium resolution Landsat, to provide fractional cover data. Hence, there is a lack of spatio-temporal mixed-pixel analysis for savannas at high spatial resolutions. Methods used for mixed-pixel analysis include parametric and non-parametric methods which range from pixel-unmixing models, such as linear spectral mixture analysis (SMA), time series decomposition, empirical methods to link the green vegetation parameters with Vegetation Indices (VIs), and machine learning methods, such as regression trees (RT) and random forests (RF). Most studies were undertaken at local and regional scale, highlighting a research gap for savanna mixed pixel studies at national, continental, and global level. Parametric methods for modeling spatio-temporal mixed pixel analysis were preferred for coarse to medium resolution remote sensing data, while non-parametric methods were preferred for very high to high spatial resolution data. The review indicates a gap for long time series spatio-temporal mixed-pixel analysis of savannas using high resolution data at various scales. There is potential to harmonize the available low resolution EO data with new high-resolution sensors to provide long time series of the savanna mixed pixel, which, according to this review, is missing.

Emerging Role of Ultrasound in Dysphagia Assessment and Intervention: A Narrative Review

Ultrasonography has gained increasing attention as a non-invasive and radiation-free instrument for the assessment of swallowing function. In the past decades, an extensive repertoire of ultrasonographic techniques, such as, B-mode dynamic scanning, pixel analysis, M-mode, Doppler, 3D reconstruction, and sonoelastography, has been applied in the evaluation of oropharyngeal structures and movement. Yet, a universal consensus on the examination protocols and clinical implications remains to be established. This review aimed to provide a brief introduction of the application of ultrasound in dysphagia assessment and intervention, encompassing the ultrasonography of swallowing-related muscles, tongue movement, and hyolaryngeal excursion, as well as ultrasound-guided interventions in the management of dysphagia. In addition to non-invasiveness, ultrasonography, a portable, easy to use, and low-cost technique, could compliment videofluoroscopic swallowing study as a first-line screening and follow-up tool for the evaluation of swallowing function, although further study is warranted to provide quantitative diagnostic and prognostic values. Finally, ultrasonography aids in the precisely targeted injection of botulinum toxin in patients exhibiting oropharyngeal muscle spasticity.

Delineation of Blood Vessels in Coronary Artery Region for Classification of Different Types of Plaques

Cardiac arrest in human arises owing to blood vessel diseases or heart defects. Blood vessel diseases result due to the blockage of blood in the heart vessels, which leads to pain in the heart. Heart defects occur because of damage in the cardiac muscles indicated by abnormal heart rhythms. Cardiovascular diseases cause mortality which could be avoided through the earlier detection of cardiovascular diseases. The major cause for cardiovascular diseases is cholesterol deposition inside the artery walls which later forms plaques that block the blood flow. Until now, plaques have been detected through medical imaging only after the heart attack. The plaques are blasted through angioplasty or reduced with medicine. Classification of the plaques before treatment, leads to effective medication based on the type of plaque. The sub classification of the plaque types such as rupture-prone plaque, ruptured plaque with sub occlusive thrombus, erosion-prone plaque, calcified nodule and non-plaque has been segmented and identified. In this paper, we propose a novel Spatial Fuzzy Propensity Score Matching (SFPSM) method to classify the plaques. The SFPSM method consists of clustering, ranking the cluster and region-based pixel wise analysis. Pixel analysis inspects specific regions of sub pixel points and calibrates the plaque. From the experimental results, the classification of plaque based on the 50-image data set has exhibited accuracy of 85% after validation. The plaque accuracy of classification provides the standard digital number values for the sub classification of plaques.