A sensor aided H.264 encoder tested on aerial imagery for SFM

Email Print Request Permissions Standard video coding systems currently employed in UAV (Unmanned Aerial Vehicle) and aerial drone applications do not rely on some peculiarities in terms of scene 3D model and correlation among successive frames. In particular, the observed scene is static, i.e. the camera movement is dominant, and it can often be well approximated with a plane. Moreover, camera position and orientation can be obtained from the navigation system. Therefore, correspondent points on two video frames are linked by a simple homography. This paper presents novel results obtained by a low-complexity sensor aided H.264 encoder, recently developed at CIRA and yet tested on simulated data. The proposed encoder employs a new motion estimation scheme which make use of the global motion information provided by the onboard navigation system. The homography is used in order to initialize the block matching algorithm allowing a more robust motion estimation and a smaller search window, and hence reducing the complexity. The tests are made coding real aerial imagery, captured to be used for 3D scene reconstruction. The images are acquired by an high resolution camera mounted on a small drone, flying at low altitude

Are Baseline Levels of Gas6 and Soluble Mer Predictors of Mortality and Organ Damage in Patients with Sepsis? The Need-Speed Trial Database

Soluble tyrosine kinase receptor Mer (sMer) and its ligand Growth arrest-specific protein 6 (Gas6) are predictors of mortality in patients with sepsis. Our aim is to clarify whether their measurement at emergency department (ED) presentation is useful in risk stratification. We reanalyzed data from the Need-Speed trial, evaluating mortality and the presence of organ damage according to baseline levels of sMer and Gas6. 890 patients were eligible; no association with 7-and 30-day mortality was observed for both biomarkers (p > 0.05). sMer and Gas6 levels were significantly higher in acute kidney injury (AKI) patients compared to non-AKI ones (9.8 [4.1–17.8] vs. 7.9 [3.8–12.9] ng/mL and 34.8 [26.4–47.5] vs. 29.8 [22.1–41.6] ng/mL, respectively, for sMer and Gas6), and Gas6 also emerged as an independent AKI predictor (odds ratio (OR) 1.01 [1.00–1.02]). Both sMer and Gas6 independently predicted thrombocytopenia in sepsis patients not treated with anticoagulants (OR 1.01 [1.00–1.02] and 1.04 [1.02–1.06], respectively). Moreover, sMer was an independent predictor of both prothrombin time-international normalized ratio (PT-INR) > 1.4 (OR 1.03 [1.00–1.05]) and sepsis-induced coagulopathy (SIC) (OR 1.05 [1.02–1.07]). An early measurement of the sMer and Gas6 plasma concentration could not predict mortality. However, the biomarkers were associated with AKI, thrombocytopenia, PT-INR derangement and SIC, suggesting a role in predicting sepsis-related organ damage

Unilateral hemothorax in a 46 year old South Indian male due to a giant arteriovenous hemodialysis fistula: a case report

In a patient undergoing regular hemodialysis through an arteriovenous fistula access, pleural effusion is a known long term complication. However, a unilateral hemothorax is relatively uncommon. Here we report a 46 year old male, end-stage renal disease patient, on maintenance hemodialysis, who presented with a giant brachiocephalic AV fistula in his left arm and progressive breathlessness. Radiological imaging revealed a left sided pleural effusion. Ultrasound guided aspiration revealed a hemorrhagic pleural fluid. A Doppler study of the fistula revealed a high velocity blood flow through the fistula, thereby establishing the cause of the unilateral hemothorax. Ligation of the fistula resulted in complete resolution of the hemothorax. The other possible causes for hemothorax in a dialysis patient are also discussed in this case report

Clinical decision modeling system

<p>Abstract</p> <p>Background</p> <p>Decision analysis techniques can be applied in complex situations involving uncertainty and the consideration of multiple objectives. Classical decision modeling techniques require elicitation of too many parameter estimates and their conditional (joint) probabilities, and have not therefore been applied to the problem of identifying high-performance, cost-effective combinations of clinical options for diagnosis or treatments where many of the objectives are unknown or even unspecified.</p> <p>Methods</p> <p>We designed a Java-based software resource, the Clinical Decision Modeling System (CDMS), to implement Naïve Decision Modeling, and provide a use case based on published performance evaluation measures of various strategies for breast and lung cancer detection. Because cost estimates for many of the newer methods are not yet available, we assume equal cost. Our use case reveals numerous potentially high-performance combinations of clinical options for the detection of breast and lung cancer.</p> <p>Results</p> <p>Naïve Decision Modeling is a highly practical applied strategy which guides investigators through the process of establishing evidence-based integrative translational clinical research priorities. CDMS is not designed for clinical decision support. Inputs include performance evaluation measures and costs of various clinical options. The software finds trees with expected emergent performance characteristics and average cost per patient that meet stated filtering criteria. Key to the utility of the software is sophisticated graphical elements, including a tree browser, a receiver-operator characteristic surface plot, and a histogram of expected average cost per patient. The analysis pinpoints the potentially most relevant pairs of clinical options ('critical pairs') for which empirical estimates of conditional dependence may be critical. The assumption of independence can be tested with retrospective studies prior to the initiation of clinical trials designed to estimate clinical impact. High-performance combinations of clinical options may exist for breast and lung cancer detection.</p> <p>Conclusion</p> <p>The software could be found useful in simplifying the objective-driven planning of complex integrative clinical studies without requiring a multi-attribute utility function, and it could lead to efficient integrative translational clinical study designs that move beyond simple pair wise competitive studies. Collaborators, who traditionally might compete to prioritize their own individual clinical options, can use the software as a common framework and guide to work together to produce increased understanding on the benefits of using alternative clinical combinations to affect strategic and cost-effective clinical workflows.</p

Change over time of COVID-19 hospital presentation in Northern Italy

none40After the first autochthonous case described on February 19, also in Italy the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARSCoV-2) infection rapidly circulated, mainly in the Northern regions of the country. The earliest reports on Coronavirus disease-19 (COVID-19) have described worldwide a high prevalence of severe respiratory illness [1]. A suggestive feature of COVID-19 has been a rapid progression of the respiratory impairment, leading to acute respiratory distress syndrome (ARDS) and often requiring ventilation support [2]. To date, whether clinical features at hospital presentation and outcome of COVID-19 have changed over the outbreak course is unknown. We explored this issue in a multicenter cohort of patients hospitalized for COVID-19 in Northern Italy.mixedPatti G.; Mennuni M.; Della Corte F.; Spinoni E.; Sainaghi P. P.; COVID-UPO Clinical Team; Azzolina D; Hayden E; Rognon A; Grisafi L; Colombo C; Lio V; Pirisi M; Vaschetto R; Aimaretti G; Krengli M; Avanzi GC; Balbo PE; Capponi A; Castello LM; Bellan M; Malerba M; Garavelli PL; Zeppegno P; Savoia P; Chichino G; Olivieri C; Re R; Maconi A; Comi C; Roveta A; Bertolotti M; Carriero A; Betti M; Mussa M; Borrè S; Cantaluppi V; Cantello R; Bobbio F; GavellI F.Patti, G.; Mennuni, M.; Della Corte, F.; Spinoni, E.; Sainaghi, P. P.; COVID-UPO Clinical, Team; Azzolina, D; Hayden, E; Rognon, A; Grisafi, L; Colombo, C; Lio, V; Pirisi, M; Vaschetto, R; Aimaretti, G; Krengli, M; Avanzi, Gc; Balbo, Pe; Capponi, A; Castello, Lm; Bellan, M; Malerba, M; Garavelli, Pl; Zeppegno, P; Savoia, P; Chichino, G; Olivieri, C; Re, R; Maconi, A; Comi, C; Roveta, A; Bertolotti, M; Carriero, A; Betti, M; Mussa, M; Borrè, S; Cantaluppi, V; Cantello, R; Bobbio, F; Gavelli, F

Simple Parameters from Complete Blood Count Predict In-Hospital Mortality in COVID-19

The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions

Texture analysis of blood flow maps in CT perfusion studies of NSCLC: correlation with the overall survival

Purpose: This study aims to assess the effectiveness of second-order texture features computed on CT perfusion (CTp) colorimetric maps, rather than on the original CTp sequences, as prognostic biomarkers. Methods and Materials: 15 patients with primary lung cancer underwent axial CTp examination and survival data were included in the study. Mean overall survival was calculated at 8.3 months. Blood flow (BF) values were computed using the maximum slope method; values undergoing high fitting errors were automatically removed. Seven global features based on first-order statistics and six local-based second-order statistics were computed on BF maps and k-means clustering algorithm was used to assess their correlation with overall survival (OS). Results: The inverse difference moment and the correlation are the most performing second-order features. In two examinations, the second-order features correlate with OS, where first-order features fail. These perfusion maps clearly show heterogeneity patterns, whose salient features cannot be extracted with simpler global analyses. Values of the couple of the second-order features allow achieving a linear separation between the groups of 10 patients with OS 648.3 and 5 patients having OS>8.3. Conclusions: These results show that the local-based features, computed on CTp maps where unreliable BF values have been removed, result to be a valuable prognostic factor for OS. In fact, the capability to consider the spatial relationships of perfusion values, thus, the functional heterogeneity characterizing the lesions, makes them really attractive. Accordingly, this technique applied on the texture of perfusion maps represents an encouraging step forwards to the clinical utilization of CTp