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Despeckling methods for medical ultr...

Zhang, Ju.

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Despeckling methods for medical ultrasound images

Record Type:	Electronic resources : Monograph/item
Title/Author:	Despeckling methods for medical ultrasound images/ by Ju Zhang, Yun Cheng.
Author:	Zhang, Ju.
other author:	Cheng, Yun.
Published:	Singapore :Springer Singapore : : 2020.,
Description:	xv, 142 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Introductions -- Despeckle Filters for Medical Ultrasound Images -- Wavelet and Fast Bilateral Filter Based Despeckling Method for Medical Ultrasound Images -- Despeckle Filtering of Medical Ultrasonic Images Using Wavelet and Guided Filter -- Despeckling Method for Medical Images Based on Wavelet and Trilateral Filter -- Nonsubsampled Shearlet and Guided Filter Based Despeckling Method for Medical Ultrasound Images.
Contained By:	Springer eBooks
Subject:	Diagnostic ultrasonic imaging - Image quality. -
Online resource:	https://doi.org/10.1007/978-981-15-0516-4
ISBN:	9789811505164

Despeckling methods for medical ultrasound images
Zhang, Ju.

Despeckling methods for medical ultrasound images[electronic resource] /by Ju Zhang, Yun Cheng. - Singapore :Springer Singapore :2020. - xv, 142 p. :ill. (some col.), digital ;24 cm.

Introductions -- Despeckle Filters for Medical Ultrasound Images -- Wavelet and Fast Bilateral Filter Based Despeckling Method for Medical Ultrasound Images -- Despeckle Filtering of Medical Ultrasonic Images Using Wavelet and Guided Filter -- Despeckling Method for Medical Images Based on Wavelet and Trilateral Filter -- Nonsubsampled Shearlet and Guided Filter Based Despeckling Method for Medical Ultrasound Images.

Based upon the research they have conducted over the past decade in the field of denoising processes for medical ultrasonic imaging, in this book, the authors systematically present despeckling methods for medical ultrasonic images. Firstly, the respective methods are reviewed and divided into five categories. Secondly, after introducing some basic mathematical tools such as wavelet and shearlet transforms, the authors highlight five recently developed despeckling methods for medical ultrasonic images. In turn, simulations and experiments for clinical ultrasonic images are presented for each method, and comparison studies with other well-known existing methods are conducted, showing the effectiveness and superiority of the new methods. Students and researchers in the field of signal and image processing, as well as medical professionals whose work involves ultrasonic diagnosis, will greatly benefit from this book. Familiarizing them with the state of the art in despeckling methods for medical ultrasonic images, it offers a useful reference guide for their study and research work.

ISBN: 9789811505164

Standard No.: 10.1007/978-981-15-0516-4doiSubjects--Topical Terms:

3444498
Diagnostic ultrasonic imaging
--Image quality.

LC Class. No.: RC78.7.U4

Dewey Class. No.: 616.07543

Despeckling methods for medical ultrasound images
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245 1 0 $a Despeckling methods for medical ultrasound images $h [electronic resource] / $c by Ju Zhang, Yun Cheng.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a xv, 142 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Introductions -- Despeckle Filters for Medical Ultrasound Images -- Wavelet and Fast Bilateral Filter Based Despeckling Method for Medical Ultrasound Images -- Despeckle Filtering of Medical Ultrasonic Images Using Wavelet and Guided Filter -- Despeckling Method for Medical Images Based on Wavelet and Trilateral Filter -- Nonsubsampled Shearlet and Guided Filter Based Despeckling Method for Medical Ultrasound Images.
520 $a Based upon the research they have conducted over the past decade in the field of denoising processes for medical ultrasonic imaging, in this book, the authors systematically present despeckling methods for medical ultrasonic images. Firstly, the respective methods are reviewed and divided into five categories. Secondly, after introducing some basic mathematical tools such as wavelet and shearlet transforms, the authors highlight five recently developed despeckling methods for medical ultrasonic images. In turn, simulations and experiments for clinical ultrasonic images are presented for each method, and comparison studies with other well-known existing methods are conducted, showing the effectiveness and superiority of the new methods. Students and researchers in the field of signal and image processing, as well as medical professionals whose work involves ultrasonic diagnosis, will greatly benefit from this book. Familiarizing them with the state of the art in despeckling methods for medical ultrasonic images, it offers a useful reference guide for their study and research work.
650 0 $a Diagnostic ultrasonic imaging $x Image quality. $3 3444498
650 1 4 $a Signal, Image and Speech Processing. $3 891073
650 2 4 $a Biomedical Engineering and Bioengineering. $3 3381533
650 2 4 $a Ultrasound. $3 894572
700 1 $a Cheng, Yun. $3 3170680
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-981-15-0516-4
950 $a Engineering (Springer-11647)