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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.
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 MATLABTM
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 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 books.
Table of Contents: Preface / Acknowledgments / List of Symbols /
List of Abbreviations / Introduction to Speckle Noise in Ultrasound
Imaging and Video / Basics of Evaluation Methodology / Linear
Despeckle Filtering / Nonlinear Despeckle Filtering / Diffusion
Despeckle Filtering / Wavelet Despeckle Filtering / Evaluation of
Despeckle Filtering / Summary and Future Directions / References /
Authors' Biographies
Ultrasound imaging technology has experienced a dramatic change in
the last 30 years. Because of its non-invasive nature and
continuing improvements in image quality, ultrasound imaging is
progressively achieving an important role in the assessment and
characterization of cardiovascular imaging. Speckle is inherent in
ultrasound imaging giving rise to a granular appearance instead of
homogeneous, flat shades of gray, as is visible and as such,
speckle can severely compromise interpretation of ultrasound
images, particularly in discrimination of small structures. On the
other hand, speckle can be used in the detection of time varying
phenomena, or tracking tissue motion. The objective of this book is
to provide a reference edited volume covering the whole spectrum of
speckle phenomena, theoretical background and modelling, algorithms
and selected applications in cardiovascular ultrasound imaging and
video processing and analysis. The book is organized under the
following four parts, Part I: Introduction to Speckle Noise; Part
II: Speckle Filtering; Part III: Speckle Tracking; Part IV:
Selected Applications in Cardiovascular Imaging.
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