Actions for Despeckle Filtering for Ultrasound Imaging and Video, Volume II [electronic resource] : Selected Applications, Second Edition

Email RIS file
Bookmark
Report an Issue

Despeckle Filtering for Ultrasound Imaging and Video, Volume II [electronic resource] : Selected Applications, Second Edition / by Christos P. Loizou, Constantinos S. Pattichis

Author
Loizou, Christos P.
Published
Cham : Springer International Publishing : Imprint: Springer, 2015.
Edition
2nd ed. 2015.
Physical Description
XXIV, 156 p. online resource
Additional Creators
Pattichis, Constantinos S. and SpringerLink (Online service)
Access Online

Availability

I Want It
I Want It

Finding items...

Series
Restrictions on Access
License restrictions may limit access.
Contents
Preface -- List of Symbols -- List of Abbreviations -- Introduction and Review of Despeckle Filtering -- Segmentation of the Intima-media Complex and Plaque in CCA Ultrasound Imaging and Video Following Despeckle Filtering -- Evaluation of Despeckle Filtering of Carotid Plaque Imaging and Video Based on Texture Analysis -- Wireless Video Communication Using Despeckle Filtering and HVEC -- Summary and Future Directions -- References -- Authors' Biographies .
Summary
In ultrasound imaging and video visual perception is hindered by speckle multiplicative noise that degrades the quality. Noise reduction is therefore essential for improving the visual observation quality or as a pre-processing step for further automated analysis, such as image/video segmentation, texture analysis and encoding in ultrasound imaging and video. The goal of the first book (book 1 of 2 books) was to introduce the problem of speckle in ultrasound image and video as well as the theoretical background, algorithmic steps, and the MatlabTM for the following group of despeckle filters: linear despeckle filtering, non-linear despeckle filtering, diffusion despeckle filtering, and wavelet despeckle filtering. The goal of this book (book 2 of 2 books) is to demonstrate the use of a comparative evaluation framework based on these despeckle filters (introduced on book 1) on cardiovascular ultrasound image and video processing and analysis. More specifically, the despeckle filtering evaluation framework is based on texture analysis, image quality evaluation metrics, and visual evaluation by experts. This framework is applied in cardiovascular ultrasound image/video processing on the tasks of segmentation and structural measurements, texture analysis for differentiating between two classes (i.e. normal vs disease) and for efficient encoding for mobile applications. It is shown that despeckle noise reduction improved segmentation and measurement (of tissue structure investigated), increased the texture feature distance between normal and abnormal tissue, improved image/video quality evaluation and perception and produced significantly lower bitrates in video encoding. Furthermore, in order to facilitate further applications we have developed in MATLABTM 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 monographs.
Subject(s)
Genre(s)
ISBN
9783031015243
9783031003967 (print)
9783031026522 (print)
Digital File Characteristics
text file PDF
Part Of
Springer Nature eBook
View MARC record | catkey: 47079594