Análisis e implementación de algoritmos para distorsionar imágenes con distintos tipos de ruido y aplicación de filtros en dos dimensiones para restaurarlas

El presente trabajo analiza ciertos algoritmos que sirven para la degradación de imágenes (ruido) y a su vez la recuperación de las mismas por medio de filtros predefinidos en dos dimensiones. El filtrado se convierte en una herramienta muy importante en situaciones reales. Se realizará un análisis cualitativo utilizando el Error Cuadrático Medio (MSE) el cual nos ayudará a determinar cual filtro es más eficiente que otro, y por último, se procederá a realizar un análisis cuantitativo utilizando para esto la percepción visual de un grupo de personas que nos ayudarán a determinar cual filtro es mas conveniente para la recuperación de las imágenes y se procederá a comparar ambos análisis. En este trabajo utilizaremos los siguientes ruidos: el Ruido Gaussiano, el Ruido Poisson, el Ruido Salt & Pepper, y el Ruido Speckle que degradarán las imágenes, los cuales serán analizados en el capítulo 2. Como filtros de recuperación utilizaremos: Filtro Average, Filtro Disk, Filtro Gaussiano, Filtro Motion y el Filtro Unsharp, analizados en el capitulo 3

Análisis e implementación de algoritmos para distorsionar imágenes con distintos tipos de ruido y aplicación de filtros en dos dimensiones para restaurarlas

This work analyses some algorithms for image degradation (noise aggregation) and image enhancement using predefined 2D filters. The filtering is a very useful tool in real situation. We will do an qualitative analysis using the Mean Square Error (MSE) that will allow us to determine which filter is more efficient under certain conditions; then we will do an quantitative analysis using human perception of randomly selected people that will determine which filter give the best result in image enhancement and distortion recovery. Finally we will compare the quantitative and the qualitative results

POFCM: A Parallel Fuzzy Clustering Algorithm for Large Datasets

Clustering algorithms have proven to be a useful tool to extract knowledge and support decision making by processing large volumes of data. Hard and fuzzy clustering algorithms have been used successfully to identify patterns and trends in many areas, such as finance, healthcare, and marketing. However, these algorithms significantly increase their solution time as the size of the datasets to be solved increase, making their use unfeasible. In this sense, the parallel processing of algorithms has proven to be an efficient alternative to reduce their solution time. It has been established that the parallel implementation of algorithms requires its redesign to optimise the hardware resources of the platform that will be used. In this article, we propose a new parallel implementation of the Hybrid OK-Means Fuzzy C-Means (HOFCM) algorithm, which is an efficient variant of Fuzzy C-Means, in OpenMP. An advantage of using OpenMP is its scalability. The efficiency of the implementation is compared against the HOFCM algorithm. The experimental results of processing large real and synthetic datasets show that our implementation tends to more efficiently solve instances with a large number of clusters and dimensions. Additionally, the implementation shows excellent results concerning speedup and parallel efficiency metrics. Our main contribution is a Fuzzy clustering algorithm for large datasets that is scalable and not limited to a specific domain

Use of early corticosteroid therapy on ICU admission in patients affected by severe pandemic (H1N1)v influenza A infection

Introduction: Early use of corticosteroids in patients affected by pandemic (H1N1)v influenza A infection, although relatively common, remains controversial. Methods: Prospective, observational, multicenter study from 23 June 2009 through 11 February 2010, reported in the European Society of Intensive Care Medicine (ESICM) H1N1 registry. Results: Two hundred twenty patients admitted to an intensive care unit (ICU) with completed outcome data were analyzed. Invasive mechanical ventilation was used in 155 (70.5%). Sixty-seven (30.5%) of the patients died in ICU and 75 (34.1%) whilst in hospital. One hundred twenty-six (57.3%) patients received corticosteroid therapy on admission to ICU. Patients who received corticosteroids were significantly older and were more likely to have coexisting asthma, chronic obstructive pulmonary disease (COPD), and chronic steroid use. These patients receiving corticosteroids had increased likelihood of developing hospital-acquired pneumonia (HAP) [26.2% versus 13.8%, p < 0.05; odds ratio (OR) 2.2, confidence interval (CI) 1.1-4.5]. Patients who received corticosteroids had significantly higher ICU mortality than patients who did not (46.0% versus 18.1%, p < 0.01; OR 3.8, CI 2.1-7.2). Cox regression analysis adjusted for severity and potential confounding factors identified that early use of corticosteroids was not significantly associated with mortality [hazard ratio (HR) 1.3, 95% CI 0.7-2.4, p = 0.4] but was still associated with an increased rate of HAP (OR 2.2, 95% CI 1.0-4.8, p < 0.05). When only patients developing acute respiratory distress syndrome (ARDS) were analyzed, similar results were observed. Conclusions: Early use of corticosteroids in patients affected by pandemic (H1N1)v influenza A infection did not result in better outcomes and was associated with increased risk of superinfections. associated with mortality [hazard ratio (HR) 1.3, 95% CI 0.7-2.4, p = 0.4] but was still associated with an increased rate of HAP (OR 2.2, 95% CI 1.0-4.8, p < 0.05). When only patients developing acute respiratory distress syndrome (ARDS) were analyzed, similar results were observed. Conclusions: Early use of corticosteroids in patients affected by pandemic (H1N1)v influenza A infection did not result in better outcomes and was associated with increased risk of superinfections. \ua9 Copyright jointly held by Springer and ESICM 2010

Association between administration of IL-6 antagonists and mortality among patients hospitalized for COVID-19 : a meta-analysis

IMPORTANCE Clinical trials assessing the efficacy of IL-6 antagonists in patients hospitalized for COVID-19 have variously reported benefit, no effect, and harm. OBJECTIVE To estimate the association between administration of IL-6 antagonists compared with usual care or placebo and 28-day all-cause mortality and other outcomes. DATA SOURCES Trials were identified through systematic searches of electronic databases between October 2020 and January 2021. Searches were not restricted by trial status or language. Additional trials were identified through contact with experts. STUDY SELECTION Eligible trials randomly assigned patients hospitalized for COVID-19 to a group in whom IL-6 antagonists were administered and to a group in whom neither IL-6 antagonists nor any other immunomodulators except corticosteroids were administered. Among 72 potentially eligible trials, 27 (37.5%) met study selection criteria. DATA EXTRACTION AND SYNTHESIS In this prospectivemeta-analysis, risk of biaswas assessed using the Cochrane Risk of Bias Assessment Tool. Inconsistency among trial results was assessed using the I-2 statistic. The primary analysis was an inverse variance-weighted fixed-effects meta-analysis of odds ratios (ORs) for 28-day all-cause mortality. MAIN OUTCOMES AND MEASURES The primary outcome measurewas all-cause mortality at 28 days after randomization. There were 9 secondary outcomes including progression to invasive mechanical ventilation or death and risk of secondary infection by 28 days. RESULTS A total of 10 930 patients (median age, 61 years [range of medians, 52-68 years]; 3560 [33%] were women) participating in 27 trials were included. By 28 days, there were 1407 deaths among 6449 patients randomized to IL-6 antagonists and 1158 deaths among 4481 patients randomized to usual care or placebo (summary OR, 0.86 [95% CI, 0.79-0.95]; P =.003 based on a fixed-effects meta-analysis). This corresponds to an absolute mortality risk of 22% for IL-6 antagonists compared with an assumed mortality risk of 25% for usual care or placebo. The corresponding summary ORs were 0.83 (95% CI, 0.74-0.92; P <.001) for tocilizumab and 1.08 (95% CI, 0.86-1.36; P =.52) for sarilumab. The summary ORs for the association with mortality compared with usual care or placebo in those receiving corticosteroids were 0.77 (95% CI, 0.68-0.87) for tocilizumab and 0.92 (95% CI, 0.61-1.38) for sarilumab. The ORs for the association with progression to invasive mechanical ventilation or death, compared with usual care or placebo, were 0.77 (95% CI, 0.70-0.85) for all IL-6 antagonists, 0.74 (95% CI, 0.66-0.82) for tocilizumab, and 1.00 (95% CI, 0.74-1.34) for sarilumab. Secondary infections by 28 days occurred in 21.9% of patients treated with IL-6 antagonists vs 17.6% of patients treated with usual care or placebo (OR accounting for trial sample sizes, 0.99; 95% CI, 0.85-1.16). CONCLUSIONS AND RELEVANCE In this prospectivemeta-analysis of clinical trials of patients hospitalized for COVID-19, administration of IL-6 antagonists, compared with usual care or placebo, was associated with lower 28-day all-cause mortality