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- W5930527 abstract "In cardiology, ultrasound is rapidly becoming one of the most soughtafter tool to investigate cardiac performance. Echocardiogram, orcardiac ultrasound, has many advantages and plays an important rolein studies concerning heart disease. Nevertheless, speckle noise,poor contrast, and artifacts in echocardiogram hamper humaninterpretation and impede automated analysis. The image qualitydegradation has rendered echocardiogram boundary enhancementnecessary. However, edges in echocardiogram are identified withambiguous spatial and intensity information that pose challenges formethods that depend on conventional gradient approximations.Although many other techniques have been proposed to improvespeckle tarnished images, most of them are problem-oriented andhold certain compromise. Many techniques commonly take tentativesolutions by making trade-off between noise suppression and edgedetection while some others are motivated by statistics and subject tonoise modeling error. Apart from that, there are also techniquesavailable which require time consuming manual definition and areliable to observer variability. Therefore, two different approachesincorporating fuzzy-based methods are proposed to automate theboundary enhancement process and reduce the commonlyencountered drawbacks aforementioned. The first approach employsa multiscale scheme to resolve the uncertainty in the informationobtained across scales so as to localize the features at low scalesand minimize noise at higher scales. In the proposed multiscaleanalysis, fuzzy reasoning provides a mean to combine the derivativeinformation of various scales stored in a filter bank. By doing so, theproposed approach reduces the trade-off between noise suppressionand edge detection that is inherent in fixed scale operators. On theother hand, the second approach attempts to take advantage of thehighly intuitive and appealing aspect of edge definition inechocardiogram by manipulating the local image characteristics.Edges in noise tarnished echocardiogram manifest themselvesdifferently from the standard definition that typically characterizesedges in an image as abrupt changes in gray-level. Nevertheless, theambiguous edge definition allows the second fuzzy-based approachto work on different edge notions that are defined by operators basedon local statistics in the image. All the proposed methods arecomprised of a comprehensive series of noise suppression, fuzzyreasoning and boundary extraction operations. Some of the proposedboundary enhancement methods are also optimized by a neuro-fuzzysystem with learning capability. The results of the proposed methodsare compared with each other and to that of a conventional methodfor performance evaluation. The results are compared subjectively byvisual observation for qualitative performance analysis. In addition,the results are measured using a standard performance index forquantitative comparison." @default.
- W5930527 created "2016-06-24" @default.
- W5930527 creator A5034980821 @default.
- W5930527 date "2007-01-01" @default.
- W5930527 modified "2023-09-27" @default.
- W5930527 title "Fuzzy-based echocardiogram boundary enhancement" @default.
- W5930527 hasPublicationYear "2007" @default.
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