Titlebook: Despeckle Filtering for Ultrasound Imaging and Video, Volume II; Selected Application Christos P. Loizou,Constantinos S. Pattichis Book 201

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https://doi.org/10.1007/978-1-4614-1114-7he kNN classifier, which are used to evaluate despeckle filtering (see also companion volume I [1]) on imaging and video. Finally, the procedure of visual despeckle filtering evaluation carried out by experts is presented.

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https://doi.org/10.1007/978-1-4614-1114-7the new High Efficiency Video Coding (HEVC) standard, the use of despeckle filtering facilitates significant bitrate gains for equivalent clinical quality, which can provide for beyond high-definition (HD) real-time communication of ultrasound video over emerging wireless networks. The presented study is based on [188–190].

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Carl C. Gaither,Alma E. Cavazos-Gaitherented in Chapters 2 to 4. The summary is based on the ultrasound imaging and video segmentation performance of the IMC and the atherosclerotic carotid plaque (see Chapter 2), on the results for texture analysis and image/video quality evaluation (see Chapter 3) and on the findings for the wireless u

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Introduction and Review of Despeckle Filtering, in Volume I of this book [1]. A despeckle filtering evaluation protocol is proposed, a brief literature review, as well as the image despeckle filtering toolbox (IDF) [2] and the video despeckle filtering (VDF) [3] software toolbox are presented. Moreover, selected applications for ultrasound image