Semantic Approach in Image Change Detection

International audienceChange detection is a main issue in various domains, and especially for remote sensing purposes. Indeed, plethora of geospatial images are available and can be used to update geographical databases. In this paper, we propose a classification-based method to detect changes between a database and a more recent image. It is based both on an efficient training point selection and a hierarchical decision process. This allows to take into account the intrinsic heterogeneity of the objects and themes composing a database while limiting false detection rates. The reliability of the designed framework method is first assessed on simulated data, and then successfully applied on very high resolution satellite images and two land-cover databases

Dietary α‐Linolenic Acid, Marine ω‐3 Fatty Acids, and Mortality in a Population With High Fish Consumption: Findings From the PREvención con DIeta MEDiterránea (PREDIMED) Study

Background: Epidemiological evidence suggests a cardioprotective role of α‐linolenic acid (ALA), a plant‐derived ω‐3 fatty acid. It is unclear whether ALA is beneficial in a background of high marine ω‐3 fatty acids (long‐chain n‐3 polyunsaturated fatty acids) intake. In persons at high cardiovascular risk from Spain, a country in which fish consumption is customarily high, we investigated whether meeting the International Society for the Study of Fatty Acids and Lipids recommendation for dietary ALA (0.7% of total energy) at baseline was related to all‐cause and cardiovascular disease mortality. We also examined the effect of meeting the society's recommendation for long‐chain n‐3 polyunsaturated fatty acids (≥500 mg/day). Methods and Results: We longitudinally evaluated 7202 participants in the PREvención con DIeta MEDiterránea (PREDIMED) trial. Multivariable‐adjusted Cox regression models were fitted to estimate hazard ratios. ALA intake correlated to walnut consumption (r=0.94). During a 5.9‐y follow‐up, 431 deaths occurred (104 cardiovascular disease, 55 coronary heart disease, 32 sudden cardiac death, 25 stroke). The hazard ratios for meeting ALA recommendation (n=1615, 22.4%) were 0.72 (95% CI 0.56–0.92) for all‐cause mortality and 0.95 (95% CI 0.58–1.57) for fatal cardiovascular disease. The hazard ratios for meeting the recommendation for long‐chain n‐3 polyunsaturated fatty acids (n=5452, 75.7%) were 0.84 (95% CI 0.67–1.05) for all‐cause mortality, 0.61 (95% CI 0.39–0.96) for fatal cardiovascular disease, 0.54 (95% CI 0.29–0.99) for fatal coronary heart disease, and 0.49 (95% CI 0.22–1.01) for sudden cardiac death. The highest reduction in all‐cause mortality occurred in participants meeting both recommendations (hazard ratio 0.63 [95% CI 0.45–0.87]). Conclusions: In participants without prior cardiovascular disease and high fish consumption, dietary ALA, supplied mainly by walnuts and olive oil, relates inversely to all‐cause mortality, whereas protection from cardiac mortality is limited to fish‐derived long‐chain n‐3 polyunsaturated fatty acids. Clinical Trial Registration URL: http://www.Controlled-trials.com/. Unique identifier: ISRCTN35739639

Cardiopoietic cell therapy for advanced ischemic heart failure: results at 39 weeks of the prospective, randomized, double blind, sham-controlled CHART-1 clinical trial

Cardiopoietic cells, produced through cardiogenic conditioning of patients' mesenchymal stem cells, have shown preliminary efficacy. The Congestive Heart Failure Cardiopoietic Regenerative Therapy (CHART-1) trial aimed to validate cardiopoiesis-based biotherapy in a larger heart failure cohort

Mining multispectral aerial images for automatic detection of strategic bridge locations for disaster relief missions

We propose in this paper an image mining technique based on multispectral aerial images for automatic detection of strategic bridge locations for disaster relief missions. Bridge detection from aerial images is a key landmark that has vital importance in disaster management and relief missions. UAVs have been increasingly used in recent years for various relief missions during the natural disasters such as floods and earthquakes and a huge amount of multispectral aerial images are generated by UAVs in the missions. Being a multi- stage technique, our method utilizes these multispectral aerial images for identifying patterns for effective mining of bridge locations. Experimental results on real-world and synthetic images are conducted to demonstrate the effectiveness of our proposed method, showing that it is 40% faster than the existing Automatic Target Recognition (ATR) systems and can achieve a 95% accuracy. Our technique is believed to be able to help accelerate and enhance the effectiveness of the relief missions carried out during disasters