This paper describes an echocardiogram coding method that takes into account the visualization modes in order to compress efficiently the echocardiogram, a methodology to evaluate compressed echocardiograms and the evaluation of the compression method using the proposed evaluation methodology. The compression method takes advantage of the particular characteristics of each visualization mode and uses different compression techniques for each mode to compress efficiently the echocardiogram. A complete evaluation has been designed in order to recommend a minimum transmission rate for each operation mode that guarantees sufficient clinical quality. The evaluation of the echocaradiograms compressed with the proposed method has been carried out. The recommended transmission rates have been established as the following: 200 kbps for the 2D and the color Doppler modes, and 40 kbps for the M and the pulsed/continuous Doppler modes. These rates, especially the latter, are very low compared to previous results. These recommendations are valid for all devices and images compressed with the proposed method. The evaluation process can be applied to any compression method.
An important topic in evolutionary art is the development of systems that can mimic the aesthetics decisions made by human begins, e.g., fitness evaluations made by humans using interactive evolution in generative art. This paper focuses on the analysis of several datasets used for aesthetic prediction based on ratings from photography websites and psychological experiments. Since these datasets present problems, we proposed a new dataset that is a subset of DPChallenge.com. Subsequently, three different evaluation methods were considered, one derived from the ratings available at DPChallenge.com and two obtained under experimental conditions related to the aesthetics and quality of images. We observed different criteria in the DPChallenge.com ratings, which had more to do with the photographic quality than with the aesthetic value. Finally, we explored learning systems other than state-of-the-art ones, in order to predict these three values. The obtained results were similar to those using state-of-the-art procedures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.