Footnote:
Part of: Synthesis digital library of engineering and computer science. - Includes bibliographical references (pages 139-151). - Compendex. INSPEC. Google scholar. Google book search. - Title from PDF title page (viewed on April 26, 2015)
1. Introduction to speckle noise in ultrasound imaging and video -- 1.1 A brief review of ultrasound imaging and video -- 1.1.1 Basic principles of ultrasound imaging and video -- 1.1.2 Ultrasound modes -- 1.1.3 Image and video quality and resolution -- 1.1.4 Limitations of ultrasound imaging and video -- 1.2 Speckle noise -- 1.2.1 Physical properties and pattern of speckle noise -- 1.2.2 Speckle noise modeling -- 1.2.3 Early attempts of despeckle filtering in different modalities and ultrasound imaging and video -- 1.2.4 Speckle noise tracking -- 1.3 An overview of despeckle filtering techniques -- 1.4 Limitations of despeckle filtering techniques -- 1.5 Guide to book contents --
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System requirements: Adobe Acrobat Reader
Description:
It is well known that speckle is a multiplicative noise that degrades image and video quality and the visual expert's evaluation in ultrasound imaging and video. This necessitates the need for robust despeckling image and video techniques for both routine clinical practice and tele-consultation. The goal for this book (book 1 of 2 books) is to introduce the problem of speckle occurring in ultrasound image and video as well as the theoretical background (equations), the algorithmic steps, and the MATLAB code for the following group of despeckle filters: linear filtering, nonlinear filtering, anisotropic diffusion filtering, and wavelet filtering. This book proposes a comparative evaluation framework of these despeckle filters based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts. Despeckle noise reduction through the application of these filters will improve the visual observation quality or it may be used as a pre-processing step for further automated analysis, such as image and video segmentation, and texture characterization in ultrasound cardiovascular imaging, as well as in bandwidth reduction in ultrasound video transmission for telemedicine applications. The aforementioned topics will be covered in detail in the companion book to this one. Furthermore, in order to facilitate further applications we have developed in MATLAB two different toolboxes that integrate image (IDF) and video (VDF) despeckle filtering, texture analysis, and image and video quality evaluation metrics. The code for these toolsets is open source and these are available to download complementary to the two books.